#java DSA course

[softcrayons4455]

Think in Code: Master DSA Concepts with Java by Softcrayons

In the modern technology-focused environment, expertise in Data Structures and Algorithms (DSA) is essential for developers seeking to create efficient, optimized code. Java, a flexible and popular programming language, is an excellent companion for grasping DSA concepts, providing both simplicity and strength to transform algorithmic thoughts into reality. An investment in a focused DSA with Java course provides future programmers with vital skills to tackle intricate challenges and thrive in the competitive software development field.

The Importance of DSA with Java

DSA provides a systematic approach to tackling a variety of coding challenges. By mastering these skills, developers can write code that efficiently uses time and memory resources—key factors in building applications that perform well under heavy loads. Java, known for its cross-platform compatibility and robustness, allows students to implement data structures and algorithms in a practical, industry-relevant way. These skills are highly valued by tech companies, particularly for roles involving competitive coding or technical problem-solving.

The Significance of DSA in Java

Fundamental Data Structures: Cover foundational structures like arrays, linked lists, stacks, queues, trees, and graphs, learning when and how to use each to achieve optimal performance.

Core Algorithms: Develop proficiency in sorting, searching, and traversal algorithms, as well as advanced techniques like dynamic programming and greedy algorithms, which are crucial for efficient problem-solving.

Real-World Applications: Every module incorporates practical scenarios to demonstrate how DSA skills apply to real-world programming challenges.

Interview Preparation: Includes mock interview sessions and problem-solving exercises to reinforce understanding and prepare students for technical interviews with top companies.

Advantages of an Experiential Learning Method

Focusing heavily on practical learning, this course motivates students to apply and evaluate algorithms, improving their coding skills. Engaging assignments and programming projects offer important practice, allowing learners to improve their abilities with the support of experienced industry professionals. The organized advancement of the course and immediate feedback guarantee that students acquire a solid, practical grasp of DSA concepts in Java.

By enrolling in an extensive DSA with Java course, learners equip themselves to effectively tackle intricate issues, enhance applications and significantly influence the software development industry. With proper training, mastering DSA is a feasible objective that opens up a realm of career possibilities.

For more information visit:-https://www.softcrayons.com/data-structures-algorithms-java

[sunbeaminfo]

Master Data Structures & Algorithms with Java at Sunbeam Institute

In today’s fast-paced tech industry, having a strong foundation in Data Structures and Algorithms (DSA) is essential for anyone aiming to excel in programming and software development. Whether you're preparing for technical interviews or looking to enhance your problem-solving skills, mastering DSA with Java can give you a competitive edge. Sunbeam Institute offers a comprehensive DSA course designed to help students and professionals gain in-depth knowledge and hands-on experience.

Why Choose the DSA Course at Sunbeam?

✅ Structured Learning Approach – Our curriculum covers fundamental to advanced DSA concepts, ensuring step-by-step learning. ✅ Hands-on Coding Practice – Learn by implementing real-world problems in Java. ✅ Industry-Relevant Curriculum – Designed by experts to meet the demands of modern tech roles. ✅ Expert Guidance – Get trained by experienced instructors with deep industry knowledge. ✅ Interview Preparation – Strengthen your problem-solving skills to excel in coding interviews at top companies.

What You Will Learn

📌 Fundamentals of Data Structures – Arrays, Linked Lists, Stacks, Queues, Trees, Graphs 📌 Algorithmic Techniques – Sorting, Searching, Recursion, Dynamic Programming, Greedy Algorithms 📌 Complexity Analysis – Understand time and space complexity to optimize your code 📌 Real-World Applications – Implement DSA concepts in Java with practical projects

Who Can Enroll?

🔹 Students aiming to build a strong programming foundation 🔹 Professionals preparing for coding interviews 🔹 Developers looking to enhance their problem-solving skills 🔹 Anyone interested in mastering Data Structures and Algorithms with Java

[limatsoftsolutionsworld]

Winter-Summer Training Kolkata

Elevate your skills with Winter-Summer Training in Kolkata. Dive into immersive courses, stay ahead, and thrive in every season. Join now for a transformative learning experience.

Visit us: https://www.limatsoftsolutions.co.in/winter-summer-training-kolkata

Read More -

Location - Electronics City Phase 1, Opp, Bengaluru, Karnataka 560100

[shwetaveer]

Starting today, July 22, 2024, I'm committing to thoroughly learn Data Structures and Algorithms (DSA) with a focus on Java, aiming to complete the course within 100 days while also practicing problems on LeetCode and GeeksforGeeks (GFG).

[tccicomputercoaching]

Best Programming Courses for Beginners in Ahmedabad India

Introduction

In the present stage of the digitization world, writing computer code is considered one of the most useful skills in today's era. It is probably the best opportunity, whether for making websites or creating software for analyzing data; the scope in programming seems endless. However, a strong foundation must be laid with a good institute. Without the right guidance, even the most talented individual may struggle to build their skills effectively. This is where the Best Programming Courses for Beginners in Ahmedabad India come into play. TCCI-Tririd Computer Coaching Institute stands as a pioneering place in Ahmedabad, India, for students to start their programming ventures.

Why Choose TCCI-Tririd Computer Coaching Institute?

1. Specialized Learning Source.

TCCI has one-of-a-kind programming skills, providing world-class programming courses primarily designed for beginners. The program runs from basic concepts to more advanced programming techniques.

2. Industry-Knowledgeable Tutors

The faculties are high-standard programs for TCCI and are used to transferring such knowledge to the students.

3. A Flexible Mode of Learning

There are online classes and offline classes which the student and the working professional can use according to their needs.

4. Hands-On Learning

According to TCCI, programming is all about practice, and students are assured of hands-on coding experience with live projects and assignments.

Top Programming Courses for Beginners at TCCI

1. C Programming

C defines the whole programming languages. Learning C gives a base understanding of the concepts for beginners in loops, functions, and memory management. C is extensively used in system programming or any embedded systems.

2. C++ Programming

The concepts offered in C++ are very important for implementing object-oriented programming principles on which the entire structure of complex applications will be built. Such as classes, inheritance, polymorphism, etc.

3. Java Programming

One of the most popular programming languages is Java, and its applications include web development, mobile applications, and enterprise solutions. Here at TCCI, you will learn Java syntax, OOP principles, and how to use frameworks like Spring and Hibernate.

4. Python Programming

Python is the easiest language to learn in web development, data science, artificial intelligence, and automation. It is more than just simple syntax to advanced libraries like Pandas and NumPy with the Python course.

5. Web Development through HTML, CSS, and JavaScript

This is the perfect course for people who just want to build websites. You learn to design responsive web pages out of HTML, CSS, and JavaScript.

6. SQL and Database Management

Essentially, SQL is the management of all things databases. This course helps students understand database designs, queries, and real-world applications of such concepts.

7. Data Structures and Algorithms (DSA)

An excellent understanding of DSA helps in writing suitable code. This course covers arrays, linked lists, stacks, queues, and also sorting algorithms.

What Makes Programming Courses at TCCI Exceptional?

Small Batch Size for Strong Attention

Real-World Projects for Actual Experience

Guidance by Industry Experts

Career Opportunities after Programming Learning at TCCI

The number of career options available to a student studying programming from TCCI is vast. They include:

Software Developer

Web Developer

Data Analyst

Mobile App Developer

Freelancer

Conclusion

If you're looking for the best programming courses for beginners in Ahmedabad, India, TCCI-Tririd Computer Coaching Institute is the ultimate choice. Their structured courses, hands-on learning, and expert guidance make them the best place to start your coding journey.

Location: Bopal & Iskon-Ambli Ahmedabad, Gujarat

Call now on +91 9825618292

Visit Our Website: http://tccicomputercoaching.com/

FAQs

1. Which programming language should I learn if I am a beginner?

Depending on your career goals, you can consider C or Python as the choice for a beginner.

2. Does TCCI provide certification after the course completion?

Yes, TCCI provides a certification to the students once they complete the course.

3. How long do beginner programming courses last?

It depends on the course. Most courses last from one to three months.

4. Do courses have practical projects?

Yes, in every course, there are practical projects for real-world training.

5. Is technical background required to take part in these courses?

No, it is for complete beginners; stepwise precept guidance will be there.

[manavrachnaonlinedegreecourses]

Essential Programming Skills You’ll Learn in an MCA Online Degree

The Master of Computer Applications online degree is designed to equip students with strong programming skills. It prepares them for careers in software development and IT consulting. It also trains them for emerging tech domains. The curriculum includes foundational programming languages and advanced coding concepts. They also learn core software development methodologies. Here is a look at the key programming skills you will master during an MCA online degree.

1. Object-Oriented Programming and Core Java

Java is a standard in UGC-approved online degree courses in India due to its prevalence in enterprise software and Android app development. You will study:

OOP principles such as encapsulation, inheritance, polymorphism, and abstraction.

Java frameworks such as Spring and Hibernate for web development.

Exception handling and multithreading to develop efficient, stable applications.

2. Python and Data Science Basics

Due to the increasing significance of AI, data science, and machine learning, MCA courses focus on Python programming. You will study:

Python syntax and libraries for data manipulation.

Machine learning fundamentals using Scikit and TensorFlow.

Automation and scripting to improve software development productivity.

3. Web Development: Frontend and Backend Programming

Web development is a critical component of an MCA curriculum, including:

Frontend technologies: HTML, CSS, JavaScript, React, and Angular.

Backend programming: PHP, Node.js, Django, and Express.js.

Database interaction with SQL, MongoDB, and Firebase.

4. Data Structures and Algorithms (DSA)

DSA is the foundation of programming for optimising code and enhancing system performance. Major topics are:

Sorting and searching algorithms (QuickSort, MergeSort, Binary Search).

Graph algorithms (Dijkstra's algorithm, BFS, DFS).

Dynamic programming to efficiently solve complex computational problems.

5. Database Management and SQL

UGC-approved online degree courses in India cover SQL and NoSQL databases to manage structured and unstructured data. You will work with:

Relational databases: MySQL, PostgreSQL.

NoSQL databases: MongoDB, Cassandra.

Database optimisation techniques for efficient query execution.

6. Mobile App Development

Most MCA graduates opt for mobile app development learning:

Android app development with Java/Kotlin.

iOS development with Swift.

Cross-platform tools such as Flutter and React Native.

Final Thoughts

An online MCA degree offers exhaustive programming knowledge that equips you with practical solutions to real-world software development problems. To become a full-stack developer, AI expert, or cybersecurity analyst, these skills will leave you well-positioned in the technology sector.

[mitscollege]

Building the Way to Success in Tech for BCA Students

The tech industry is booming, and opportunities abound-from software development and data analytics to cybersecurity and cloud computing. For the BCA student this field is no doubt interesting but very competitive. What makes the cut to be unique and successful within a tech industry is beyond a degree - it demands a harmonious blend of skills, experience, and strategic planning. Today, with this blog post, we'll know the key tips through which BCA students can carve out a successful tech career by honing technical skills, good networking, and staying updated with the changing trends in the industry.

1. Master the Fundamentals of Programming and Problem-Solving

Well, basically, programming forms the backbone of the tech industry, and when it comes to a student studying BCA, it becomes important to master the same in order to have an excellent career. Along with the course of your BCA, you are taught various programming languages like C, C++, Java, Python, and other programming languages. Try to master all because most of the tech jobs are covered by these programming languages, whether it is software development, web development, or data science.

Practice HackerRank, LeetCode, and Codeforces are platforms you can practice coding regularly. It helps develop your problem-solving skills and learn algorithms more efficiently. Work on projects. Making your own websites, applications, or software will provide hands-on experience and the chance to apply what's learned to real-world situations.

Participate in Coding Contests: One should really attempt CodeChef and Google's Kick Start since that is the best place to test oneself and hone the coding skills and shine for employers. Remember, the employers value both problem-solving as much as the programming aspect so, logical thinking and finding the most optimum solution to complex problems shall always be key.

2. Strong Base in Data Structures and Algorithms

One of the most crucial aspects of computer science and programming is DSA- data structures and algorithms. Once you grasp DSA, your ability to write code allows its execution as efficiently and optimized as possible, and therefore, very critical in developing scalable software and systems. In fact, the tech companies such as Google, Amazon, and Microsoft are keen on DSA during their hiring process.

Learn Basics: Begin by learning the fundamental data structure, like arrays, linked lists, stacks, queues, hash tables, and binary trees. Practice writing each of them from scratch in many programming languages.

Master Algorithms: Learn typical algorithms like sorting, searching, and recursion. Study the more advanced topics of dynamic programming, greedy algorithms, and graph traversal algorithms.

Practice Problems: GeeksforGeeks, InterviewBit, and LeetCode are platforms that offer structured DSA practice problems across multiple levels of difficulties. Start with easy problems and keep moving on to more challenging levels. DSA is not only a technical interview preparation but also helps in designing systems in a much better way in the workplace.

3. Learn Beyond the Classroom: Explore New Technologies

As your BCA programme will allow you a great foundation in key areas such as programming, database management and web development, do not take this as the only major happenings out there in the tech space, since new technologies and tools are surfacing every single day. For these purposes, you might consider exploring some of them.

Technologies to explore:

Some of the prominent ones existing in the market today are AWS, Microsoft Azure, and Google Cloud. Thus, you would really learn how to deploy and manage your cloud infrastructure to get a career in the field of cloud computing and DevOps. Artificial Intelligence and Machine Learning: AI and ML are changing the face of industries like healthcare, finance, and e-commerce. But by learning Python, TensorFlow, and other tools for AI and ML, it would be possible to build predictive models and, consequently, develop AI-driven applications.

Blockchain: With increasing applications in the finance sector, supply chain management, and security, blockchain technology is getting popular. Understanding how blockchain works and building smart contracts on platforms like Ethereum will put you at an edge in this niche.

Cybersecurity: Increasing cases of cyber threats demand lots of cybersecurity skills. Thus, one should opt for courses like network security, ethical hacking, and data encryption to stand out in the niche of cybersecurity.

You will be in a position to understand and cope with industry changes and be placed in specialization roles that could best fit your interest.

4. Learn through Internships

This will enable you to interact with new technologies and know how you can adapt them into your daily practice.

Internships will give you real-world experience in which you will be using everything you have learned. You will also get to know different roles, industries, and technologies that can help you in your chosen path. But most of all, they can really make your resume spectacularly jump at the face of any hiring manager for a full-time job after graduation.

How to find and excel in internships:

**Tapping into Networking: Reach out to professors, alumni, and business professionals for the purpose of locating an internship. Utilize LinkedIn in building connections with possible employers and seek out job openings. Apply Early: Start searching for internships early because most companies post their applications months before the actual date the internship is set to start.

Be Proactive: After you get the internship, it is not just about taking advantage of being at a good organization but also to your benefit, it presents an opportunity to bring value. Engage in real projects, learn from feedback, and most importantly, seize opportunities during your period of mentorship.

That experience, no matter how small you start with - whether paid or unpaid internships - will eventually pay dividends in the long term because it adds to your list of skills and professional experiences.

5. Acquire Soft Skills Along With Technical Skills

With technical skills, one might achieve partial fulfillment of success in the tech industry. Soft skills are equally important, such as good communication, team working, time management, and problem-solving skills, without which a technical professional will not be able to fly high in that industry. When working in a team environment, proper explanation of the technical concepts to nontechnical stakeholders, managing projects properly, and working with heterogeneous groups is a major requirement.

Key soft skills to focus on :

Communication: Learn how to communicate technical ideas in both writing and speaking.

Teamwork: Most of the work in tech involves teamwork. You will work with designers, marketers, and project managers. All these will help you gain great interpersonal skills.

Time Management: Deadlines and multiple projects at once are some of the regular phenomena. Proper time management helps target priorities and work effectively.

A balance between your technical and soft skills will make you a more diversified candidate, thereby making you more employable in the highly competitive job market.

6. Portfolio and Personal Branding

A diversified portfolio, showing off your skills, projects, and experiences, will differentiate you from other applicants. It should prove that you can solve problems, write clean code, and deliver high-quality projects.

What to include:

Personal Projects: Make sure to describe and include code for personal and class projects worked on. It's better to have a few well-executed projects than many unfinished ones.

GitHub Repository: Include your GitHub profile in your resume. This provides employers with an opportunity to review your code, contributions and development practices. You can include the following in the portfolio:

Certificates: If you have undertaken some certificates that illustrate your sector of competence in a particular domain, such as cloud computing, data analytics, or cybersecurity. Include all those certificates in the portfolio

Blog or Website: If possible, create a personal website or blog whereby one can express his thoughts regarding their portfolio and may write concerning the tech topic he or she is enthusiastic about. This would help build your own brand and make you out as the source of ideas or as a thought leader in your chosen field.

7. Stay updated about current trends and network professionally

The reason for this is that the technology sector keeps changing rapidly, and awareness of cutting-edge technology is a must in order to avoid outdatedness. Update yourself regularly by reading the latest technology blogs, participating in conferences, and joining online groups to keep you posted on current technologies, the standards of the industry, and the best practices prevailing in the industry.

Staying updated and networking

Follow Tech blogs proactively: Websites like TechCrunch, Wired, and The Verge keep you abreast of new technologies, startups, and innovations. Subscribe to them for staying up-to-date.

Online Communities: Engage yourself on websites like Reddit, Stack Overflow, and GitHub, where you get to spend time with other tech professionals, ask questions, and remain updated on the industry trends.

Meetups and Conferences: Industry conferences, webinars, and meetups with the locals are fantastic ways to expand your professional network, network ideas from industry thought leaders, and perhaps discover job opportunities.

Effective networking opens doors to internships, jobs, and mentorships. Build strong networking relationships with professors, peers, and industry professionals.

8. Prepare for Job Interviews and Technical Tests

Hiring into the tech field normally comes after the candidate is able to stand out from the rest of the applicants by passing the intense technical interview and coding tests. The early preparation stage can be better done if one practices coding problems, reviews key concepts in computer science, as well as educates themselves about common questions asked.

Interview Prep Tips

Practice Mock Interviews: Mock interviews with friends or on platforms like Pramp will help you get accustomed to answering technical questions under pressure.

Revisit the Fundamentals: Practice data structures and algorithms, operating systems, database management, and networking. These are common interview hotspots.

Learn About the Company: Once you know which company you'll be interviewing with, dig up knowledge regarding its product/service, technologies, and business model. That way, you will tailor your answers to what they'll need most and show interest in their corporation.

This will equip you with greater confidence in technical and behavioral interviews.

9. Higher Education and Specialization

A BCA is a wonderful start but most continue their education further for specialisation. One may decide to pursue his or her Master's in Computer Applications (MCA), MS in Computer Science, or an MBA in Information Technology, depending on career prospects.

Advance degrees help you deepen knowledge in specialized fields like artificial intelligence, cybersecurity, data science, and cloud computing; this may boost your marketability and career prospects

Conclusion

Building an excellent tech career as a BCA student is more than just doing your course work. It will demand continued learning, practical experience, and strategic career planning. By perfecting programming skills, venturing into new technologies, getting hands-on experience, and developing relevant technical and soft skills.

[ricrbhopal]

Which Is The Best Full Stack Development Institute In Bhopal?

Full Stack Developer course in Bhopal

If you're looking to pursue a Full Stack Development course in Bhopal, Raj Institute of Coding and Robotics (RICR) stands out as a top option. Located on the 4th floor of Minal Mall, RICR is a new venture under Raj Groups and is gaining popularity among students eager to learn java Programming in Bhopal.

Why Choose RICR for Full Stack Development?

Comprehensive Course: RICR offers a Full Stack Development program that covers both front-end and back-end development. You’ll get hands-on experience with key technologies like Learn java Programming in Bhopal and the MERN stack (MongoDB, Express.js, React, Node.js). The course also includes Data Structures and Algorithms (DSA) using Java, equipping you with essential programming skills.

Tailored Learning: Not interested in the full course? No problem. You can choose to focus solely on Java coding Classes in Bhopal or Web Development. RICR allows you to customize your learning path based on your needs.

Diverse Course Offerings: In addition to Full Stack Development, RICR offers popular courses in Data Science, C and C++, and Data Analytics, giving you the flexibility to explore various in-demand skills.

Support for All Students: RICR places a special focus on students who may need extra help, offering separate batches for those who require additional support. Extra worksheets and practice sessions help build confidence and enhance skills.

Comprehensive Doubt Resolution: With experienced instructors and technical assistants on hand, RICR ensures that all your questions and doubts are resolved quickly, making the learning process smoother.

EduNest Facility: If you need extra practice or can't leave late at night, RICR provides the EduNest facility, allowing you to stay for one or two nights to focus on your learning without worrying about time constraints.

Lifetime Access to LMS: Every student at RICR gets access to the institute’s Learning Management System (LMS), which tracks individual progress. The LMS includes quizzes, assessments, and exclusive course content that you can access even after you complete the course.

Flexible Schedule: RICR operates from 11 a.m. to 9 p.m., giving you the flexibility to choose a batch that fits your schedule, whether you’re working or managing other commitments.

Affordable Fees: RICR offers courses at reasonable rates, and their counselor can provide you with all the necessary fee details.

Conclusion:

Whether your goal is to become a Full Stack Developer, master Java, or explore other tech fields like Data Science or Data Analytics, RICR offers a supportive, flexible, and affordable learning environment. With its tailored courses, strong student support, dedicated facilities like EduNest, and lifetime LMS access, RICR ensures a high-quality learning experience. Start your journey with RICR’s Aadhaar Foundation Course in Bhopal and build a strong foundation in coding and development!

[tutortacademy]

Unlock the Power of Data with DSA & System Design Course

It is essential to become proficient in programming and problem-solving in the quickly changing tech industry. Any prospective developer can discover a world of possibilities when they combine their strong Data Structures and System Design skills with Java, a versatile and powerful programming language. This blog explains the "Java DSA & System Design" journey with PW Skills and clarifies the importance of this extensive course and how it might support your coding endeavors.

Data structures and system design course foster a problem-solving mentality in addition to teaching grammar. You will be faced with real-world difficulties in this course, which call for innovative and practical answers. This improves your capacity for analytical thought, which is essential for any developer.

[wilawe]

Full Stack Web Development Course

[softcrayons4455]

Data Structures & Algorithms using JAVA

In the continuously changing realm of technology, a robust understanding of Data Structures and Algorithms (DSA) is essential for hopeful software engineers and developers. The capacity to devise effective solutions to intricate issues relies on a firm comprehension of these basic principles. Softcrayons Tech Solutions provides a carefully designed course in DSA utilizing Java to equip learners with both practical and theoretical knowledge.

Why Choose Java for DSA?

Java is famous for its ease of use, portability, and strength, which makes it a perfect language for learning DSA. Its vast library support and object-oriented characteristics allow students to implement algorithms effectively. Moreover, Java’s prevalent usage in the tech industry guarantees that the skills gained during this course are immediately relevant to practical situations.

What the Course Covers:

Core Data Structures: Arrays, Linked Lists, Stacks, Queues, Trees, Graphs, and Hash Tables.

Algorithmic Techniques: Sorting, Searching, Dynamic Programming, Backtracking, and Greedy Algorithms.

Problem-Solving: Step-by-step guidance to tackle coding challenges and optimize solutions.

Hands-On Projects: Practical assignments to solidify understanding and application of concepts.

Benefits of the Course:

Expert Mentorship: Learn from experienced instructors who provide personalized guidance.

Interactive Learning: Participate in live coding sessions and collaborative projects.

Industry Relevance: Prepare for technical interviews and enhance your career prospects.

Comprehensive Resources: Access detailed study materials and practice problems.

This course provides students with the abilities necessary to thrive in coding competitions, succeed in job interviews, and create cutting-edge software solutions. For individuals prepared to begin a path of coding achievement, this program serves as the gateway to success.

Sign up for the DSA using Java course now and turn your programming potential into mastery with Softcrayons Tech Solutions.

For more information visit:-https://www.softcrayons.com/data-structures-algorithms-java

[sunbeaminfo]

In today’s fast-paced tech industry, having a strong foundation in Data Structures and Algorithms (DSA) is essential for anyone aiming to excel in programming and software development. Whether you're preparing for technical interviews or looking to enhance your problem-solving skills, mastering DSA with Java can give you a competitive edge. Sunbeam Institute offers a comprehensive DSA course designed to help students and professionals gain in-depth knowledge and hands-on experience.

Why Choose the DSA Course at Sunbeam?

✅ Structured Learning Approach – Our curriculum covers fundamental to advanced DSA concepts, ensuring step-by-step learning. ✅ Hands-on Coding Practice – Learn by implementing real-world problems in Java. ✅ Industry-Relevant Curriculum – Designed by experts to meet the demands of modern tech roles. ✅ Expert Guidance – Get trained by experienced instructors with deep industry knowledge. ✅ Interview Preparation – Strengthen your problem-solving skills to excel in coding interviews at top companies.

What You Will Learn

📌 Fundamentals of Data Structures – Arrays, Linked Lists, Stacks, Queues, Trees, Graphs 📌 Algorithmic Techniques – Sorting, Searching, Recursion, Dynamic Programming, Greedy Algorithms 📌 Complexity Analysis – Understand time and space complexity to optimize your code 📌 Real-World Applications – Implement DSA concepts in Java with practical projects

Who Can Enroll?

🔹 Students aiming to build a strong programming foundation 🔹 Professionals preparing for coding interviews 🔹 Developers looking to enhance their problem-solving skills 🔹 Anyone interested in mastering Data Structures and Algorithms with Java

🔗 Enroll Now: https://sunbeaminfo.in/modular-courses/data-structure-algorithms-using-java 📞 Call Us: 8282829806

Take your programming skills to the next level with Sunbeam Institute’s DSA using Java course. Join today and start your journey towards becoming a proficient developer!

[rohit-69]

PW Skills Reviews – Career Tracks, Courses, Learning Mode, Fee, Reviews, Ratings and Feedback

Introduction:

The mission of PW Skills is to transform the question "How Can I Do It?" into a resounding "Of Course I Can Do It." This initiative is geared towards professionals and students, aiming to revolutionize their approach to work through top-notch upskilling courses. PW Skills endeavors to make these courses technologically advanced, affordable, and accessible to individuals everywhere, thereby enhancing their potential for success in life.

PW Skills Reviews:

According to PW Skills reviews, the platform is a comprehensive solution for upskilling, offering courses ranging from basic web development languages like HTML, CSS, and JavaScript to advanced topics such as frontend and backend development frameworks, responsive design, and database management. The platform was founded by experienced web developers and educators, evolving to cover a diverse range of skills and fostering community building through forums, live coding sessions, and mentorship programs.

Leadership:

The leadership of PW Skills is embodied by Alakh Pandey, the Founder and CEO, who envisions breaking down financial barriers in education. Prateek Maheshwari, the Co-Founder, brings a wealth of experience in educational technology and entrepreneurship. Their combined efforts have propelled PW Skills to become India's leading and most affordable ed-tech platform.

Career Tracks and Certifications:

PW Skills offers diverse career tracks in cybersecurity and information technology, including roles like cyber security analyst, network security engineer, and ethical hacker. The courses are often affiliated with reputable institutions, ensuring quality and accreditation. Furthermore, students can earn globally recognized certifications such as CompTIA Security+, CISSP, CEH, and more, enhancing their employability.

Key Features and Unique Selling Points:

PW Skills stands out through personalized courses, a broad spectrum of skill development, adaptability and reusability, high-quality educational materials, continuous progress measurement through reviews and feedback, and an active user support system.

Courses Offered:

PW Skills provides a range of courses, including C++ with DSA, Data Analytics, Decode Java+DSA 1.0, Decode Full Stack Web Dev 1.0, Decode Data Science with ML 1.0, and Data Science with Generative AI. These courses cater to different skill levels and interests, promoting a holistic learning experience.

Website Analysis:

The website design and planning could benefit from enhanced simplicity and attractiveness for improved user-friendliness. Regular content updates and improvements based on user experiences can contribute to a more engaging platform. Addressing feedback, adding features, and ensuring clear navigation are vital for an optimal user experience.

PW Skills Data Science Program:

The Data Science Program, particularly with Generative AI, offers a comprehensive understanding of data science and its applications. With industry-relevant projects, skill elevation exercises, and mentor-led live sessions, the program aims to equip participants with practical skills for data-driven decision-making and creative endeavors.

Mentors:

PW Skills boasts a team of experienced mentors, including Rishabh Malhotra, Sahil Garg, and Ekta Negi. These mentors bring a wealth of knowledge and practical experience in the field of data science, enhancing the learning experience for participants.

Pros and Cons:

Pros of PW Skills include expanded opportunities, improved job prospects, practical experience, and contributions to health and social development. Cons include variations in course quality, theoretical focus in some courses, financial costs, and concerns about certificate validity.

PW Skills Reviews on Various Platforms:

PW Skills has garnered positive reviews on platforms such as Trust Pilot and Analytics Jobs, indicating its impact and recognition within the industry.

Conclusion:

PW Skills has established itself as a prominent player in the field of cybersecurity and information technology education. With a commitment to quality, affordability, and accessibility, the platform empowers individuals to enhance their skills and pursue rewarding career paths. The positive reviews, industry partnerships, and diverse course offerings underscore the platform's success in fulfilling its mission.

If you want to know more PW Skills Reviews or courses then do visit - analyticsjobs

[tccicomputercoaching]

Key Computer Engineering Degree Courses

Computer Engineering is a vast field, merging hardware and software expertise for designing new technologies. The students at TCCI Computer Coaching Institute are prepared for the future with courses in keeping with essential topics of a Computer Engineering degree. Here are the key subjects that should be learned:

Programming Fundamentals

Languages such as C, C++, Java, and Python are basic. They train students in logical thinking and problem-solving, which are essential in software development and computational work.

Data Structures and Algorithms (DSA)

Knowing how data is structured and processed is very important to coding efficiently and solving problems. Concepts include stacks, queues, trees, and graph algorithms.

Database Management Systems (DBMS)

Learn the principles of handling data with relational databases like MySQL, PostgreSQL, and MongoDB. DBMS knowledge is crucial for backend development and in data-driven applications.

Computer Networks

It delves into communication protocols, internet functionality, and network security, preparing them to build or manage a network.

Operating Systems (OS)

A student learns how operating systems work, including memory management, process scheduling, and system security, preparing for systems programming roles.

Software Engineering

This subject focuses on software development methodologies, such as Agile practices, project management, and quality assurance.

Web Development

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AY23/24 Sem 1 Module Reviews

This sem is probably the most difficult sem of my degree acads wise. Since I scored much better than expected in Year 1, I could afford to fully focus on core modules that would teach me useful skills related to my major. Hence, I decided to take 4 core modules, namely CS2040, DSA2101, DSA2102 and MA2311, along with GEN2061X. I did slightly underload to give myself more time for CS2040, which has a very high workload. I was also expecting a drop in GPA since most of the modules I took this sem weren't exactly easy or fluff. Nonetheless, I grew much closer to the friends I worked with in the different mods, and it made all the difference to my mental well-being as well as my academic performance.

CS2040

Module Coordinator & Lecturer: Dr Chong Ket Fah

T/A: Gary (tutorial), Chao Ming (lab), Sourabh (lab)

Lecture Topics/Schedule:

Week 1: Course Admin + Intro to Java, Analysis of Algorithms 1 Week 2: Analysis of Algorithms 2, Sorting 1 Week 3: Sorting 2, List ADT 1 (Array List, Linked List, Stack, Queue) Week 4: List ADT 2 Week 5: Map ADT (HashTable) Week 6: Priority Queue ADT (Binary Heap) Week 7: Disjoint Sets ADT (Union Find Disjoint Set), Ordered Map ADT 1 (Binary Search Tree/AVL Tree) Week 8: Ordered Map ADT 2, Graph Intro + Graph DS Week 9: Graph Traversal and Applications 1 Week 10: Graph Traversal and Applications 2, Minimum Spanning Tree  Week 11: Single Source Shortest Path 1 Week 12: Single Source Shortest Path 2, All Pairs Shortest Path Week 13: Revision

Deliverables:

Tutorial attendance/participation - 3% Lab attendance - 2% One-Day Assignments (ODAs) - 1.5% x10 Take Home Assignments (THAs) 1.5% x8 qns, 2 qns per assignment Visualgo Quiz - 4% x2 Midterm - 20% Final Exam - 40%

Other Comments:

Although this module is hard (as you probably already know), I would say I enjoyed it for the most part. First of all, Dr Chong Ket Fah is an amazing lecturer, and he explains things very clearly. This made understanding the difficult concepts a lot easier. Dr Chong is also very nice and understanding towards students, for example, I fell sick one day before a one-day assignment and he extended my ODA deadline to the day after my MC ended which was basically one week later lol. These things might seem insignificant but they are highly appreciated by students (me at least).

There was a lot of content to cover in this module, and frankly, it can sometimes get overwhelming. On paper, there are 3 hours of lectures every week on Zoom exclusively, but Prof Chong often overruns to about 4-5 hours of lecture time a week. Not to worry, the lectures are recorded and you can watch them later. It is paramount that you keep up to pace with the lectures as it's not realistic to cram all of it in reading week, anyway you'll need the lecture content 1-2 weeks later to solve the ODAs and THAs. Also, we're expected to learn Java within the first 2 weeks, as prof does not teach java, he just gave us a learning package/crash course to do on our own. This is very important for students with no Java background like DSA students because we'll be expected to complete all our coding assignments in Java from end of week 2/week 3 onwards.

I attended the tutorial slot by Gary, and Gary is absolutely goated. He is very clear in explaining things, and often talks about potential extensions/modifications to the questions which may come up in the exams. This was very helpful in cultivating the sort of skills and thought process needed in the midterms/finals. Gary is also very chill and dedicated, we can message him on Telegram if we have any questions, and usually the night before the exams, he would stay up all night to answer questions that we had. Where are you gonna find such a dedicated TA HAHAHA please give this man a raise The only not-so-good thing about the tutorials is that the bulk of questions are pseudocode/coming up with algorithm questions, but the majority of questions in the exam are MCQ. I would've liked to see more of the latter in the tutorials as many of us felt unprepared for MCQ-style questions in the exams. From my understanding, the exams used to be a lot heavier in pseudocode questions, which might explain such an emphasis on such questions in the tutorial. If so, the tutorials might need a refresh.

Labs are essentially dedicated to solving ODA questions, and you can ask your lab TAs if you're stuck on either the ODAs or THAs. Apparently, they are also the ones that grade them. For me, I left my whole Friday empty in case I got stuck on an ODA and needed more time to solve it, since you have to complete in 24 hours. I also worked on the problem before my lab slot, like once the assignment opened at 10am. This was to ensure I made full use of my lab TAs expertise during the precious 2 hours if I got stuck, instead of trying to understand the question and come up with a first iteration to solve it. The ODAs in general were not terribly difficult though. As for the lab TAs, most of us preferred to talk to Chao Ming because he was more approachable and helpful. However, we often don't understand each other's algorithm suggestions HAHAHA. On the other hand, Sourabh was very passive. Maybe he was in charge of doing the assignment grading? But my friend asked him questions on telegram and got blue-ticked (I think more than once) so there's that. Oh also, you're required to submit pseudocode before or during the lab which also acts as your lab attendance grade, which is why you should start working on it before the lab because 2 hours to do pseudocode and actually code and debug is very tight.

THAs were more difficult, and I spent about 1-4 days on each question. There were 4 THAs in total, 2 questions in each THA. Discussing algorithms with friends really helps because a lot of these problems are not straightforward and require a good grasp of lecture content along with creativity. Unlike CS1010, your code now has to be efficient and meet the required run-time, otherwise it will not be accepted. Hence, talking to friends to see if there are other more efficient ways of solving the problem is highly efficient on your time needed to solve the THAs. Do note that looking at other people's code is not allowed, as mentioned by the prof so just be careful not to show actual code when discussing. The worst THA though probably has to be the AVL tree one, it was incredibly painful to have to build the AVL tree on your own and do all the rotations. Maybe deforestation isn't so bad after all Nonetheless, you should score full marks for both the ODAs and THAs as most people do after countless tries or discussing algorithms with friends.

Midterms and finals were pretty similar, exams were on Examplify and the bulk of it was MCQ questions, with 2-3 pseudocode/come-up-with-algorithm questions. The midterm tested until hashtables and was apparently harder than finals. As many of you know, Prof Chong sets hard papers so be prepared. Make sure you read the question properly as there's a lot of constraints/things to look out for to get the correct answer. Prof's questions also tend to be very long and confusing so it might take a lot of time and brain-power to understand what's going on in the question. Exams were open-book closed internet, the midterm was 1.5 hours and the final exam was 2 hours. You have to have a good grasp of the various algorithms, how they work, how their time complexities are derived and subsequently in what situations each algorithm works best/worst. I highly recommend working on the pseudocode questions at the end first because they need more time to think and come up with the solution, and if you don't know anything just write something out, and you'll get at least one mark. The MCQs can still be guessed if you run out of time, but try to do them well because they form the bulk of the marks. Do lots of PYPs to get a feel of the MCQ questions and see how the pseudocode questions should be answered. Also, for the pseudocode questions, I observed that writing in paragraphs/essay-style is much better than the usual code style because there's more ambiguity and it's easier for the marker to understand your algorithm's logic compared to code-style which will often be ridden with errors. For finals, prof actually dropped quite a few hints when he was going through the PYPs without answers in Week 13 lectures so do make sure to watch that. My score for the midterm was 58/100 (77th percentile), and the final exam was 75/95 (93rd percentile). Midterm stats 0 39 47 56 95, finals stats 0 41 50 62 91. Finals was originally out of 100, but there was an issue with the time complexity required and getting the correct answer (apparently the solution to solve it in that time complexity results in overcounting) in the last pseudocode questions, so prof re-based it to 5 instead of 10 marks and marked according to the next best algorithm to get the right answer.

Lastly, there were 2 Visualgo quizzes held during lab slots, one in Week 7 and the other in Week 13. Make sure to practise a lot of Visualgo questions in hard mode. I found the week 13 quiz much harder because the later topics were harder, especially MST. As a result, I got 14/15 for it because I got the 2nd best MST question wrong (so saddd). The first quiz was pretty easy though. Most people get full marks for both so.

All in all, I find this module difficult but also rewarding. A lot of the concepts taught are important, for example, I'm working on a project now that makes use of what I learnt in 2040. All the best to those taking it in future sems, rest assured Dr Chong is a very good prof and you're in good hands! Just put in the work and you should stay afloat

TLDR:

High workload, don't overload (in fact try to underload) when taking this mod Leave your Fridays empty to work on the ODAs Learn Java ahead of time if you can to get used to the syntax, don't leave THAs to the last minute because you need time. Discuss with friends to maximise efficiency on coding assignments Do PYPs and understand how each algo works, how the time complexity comes about, when to use what algo Do lots of Visualgo practice for the quizzes

Grades:

Expected grade: A- Actual grade: A

DSA2101

Module Coordinator & Lecturer: Dr Huang Yuting

T/A: Augustine

Lecture Topics:

R programming.

Importing data into R.

Data manipulation with R (Tidyverse)

Principles of data visualization.

Introduction to the grammar of graphics (ggplot2)

Exploring data through visualization.

Deliverables:

Tutorial Attendance - 5% DataCamp assignments - 10% Group project - 15% Midterm - 30% Finals - 40%

Other Comments:

This module has a pretty light workload, and the content is quite straightforward. It's a coding mod about data cleaning and visualisation using R. I thought I would be disadvantaged as I was pre-allocated DSA1101 in Sem 1 last year under Dr Sun, which had little coding emphasis and more stats/math, whereas in Sem 2 Dr Daisy Pham took over and revamped the whole module to essentially be about R coding. However, the first few weeks of lectures were about R coding and it was more than enough time to catch up. Also, it turns out that I'm quite quick at debugging in R, which is a great asset in exams. Dr Huang is a good lecturer in my opinion, she is concise and emphasises on the important things. Lectures are basically her going through slides which show various ways to code using a variety of tools/functions, and often she'll do a live demo to reinforce what was taught in the slides. She encourages us to code alongside her, and for this reason (apart from the fact that lectures are at 8am), I think it's better to watch the recorded lectures as you can pause and try them out yourself before continuing. Prof is also very approachable and quick to reply my emails, even if I ask a barrage of questions.

Tutorials are coding questions for you to try out on your own, and the TA will go through them. Augustine was a good TA, on top of the solutions provided by prof, he would add other methods to get the same result, and he was decent at explaining the code flow and thought process. He also responded to my queries on Telegram for the most part. As for the tutorial questions, I highly recommend trying them out on your own without using chatgpt to debug, because it's good practice for exams.

DataCamp Assignments were 8 x 1.25% online modules/courses? on DataCamp. These are free marks so just make sure you complete them by the deadline. DataCamp honestly isn't very helpful in learning because almost everything is filled in, and they just need you to fill in a few blanks.

The midterm was a 1.5-hour Examplify, open-book but closed internet exam, held in Week 8 at 8am (!!), and this was probably the most difficult part of the course. Most people weren't mentally awake at 8am, and the paper was quite difficult. It is easy to forget a certain function or have syntax errors, and R isn't the easiest language to debug in. It might be tempting to keep working on one part before moving on to the next because each sub-part leads to another, but the grading was very lenient in the sense that even if you miss out on a lot of things, you can still get the bulk of the marks. The key point is to try and complete everything and you should be above the median already. Since you don't have internet access, it is paramount that you do the tutorials as practice without the internet to prepare for the midterm. There were also a lot of small things that tripped people up, such as not being able to read the excel file in R when the excel file is open on your computer, ctrl-c ctrl-v being locked, the question paper on Examplify only taking half of the screen and couldn't be expanded etc. Overall it was a bad experience but luckily the grading was so kind. I got 27.5/30, the median was 21.25/30. Also do note that you have to copy your code from R into Examplify and differences between the R code submitted on Canvas and the Examplify code will be subjected to penalties. However, the Examplify exam does not auto-submit when time is up because there's 15 minutes after the exam to complete all the admin, so make sure your file can knit and all (basically the correct version of your R file) before you copy and paste into Examplify.

The group project was a report where we had to come out with 3 different plots using ggplot to investigate a meaningful question from one of the datasets given. We were allowed to choose our group members regardless of tutorial slot, so be sure to take this mod with friends!! My group did San Francisco Rentals, which a lot of people avoided because there were a lot of observations and variables/columns, but it turned out to be quite easy as we only had to select a few columns to work with. I had other friends who did the Lego dataset which seemed easy at first glance, but turned out to be a nightmare because you had to join a lot of different tables together to get the data you wanted. Unfortunately, I don't know why my group underperformed, I only got 12.5/15, and I assume a lot of people would get 13-15 out of 15 (stats were not released). Anyways just make sure you don't leave the project to the last minute because it can be quite tedious to code and have to write the report.

Finals were a lot easier than midterms. The format was Examplify open-book, closed-internet 2-hour exam, consisting of 25 marks of MCQ/fill-in-the-blank questions and 15 marks of coding. The coding this time around was much simpler, and possibly because we're more experienced by then. The MCQ questions were very easy, and if you were unsure of anything (eg. the definition of tidy data), you could just Ctrl-F. Hence, I recommend collating the lecture slides into one document to more efficiently Ctrl-F. This also helps for the coding questions, as there was 1 data-cleaning and 2 ggplot questions, and if you're unsure of which ggplot function to plot the graph, there's a summary on the lecture slides, alongside an example of the syntax to come up with the plot. Hence, I finished the exam with half an hour to spare and checked through my answers. I think the bell curve for this paper is quite steep because it was relatively easy. There was only one part that tripped some people up, which was removing NAs before or after performing pivot-longer. This will yield different results and affects 2 MCQ questions and the 5 mark coding question. Other than that, the exam is straightforward so be sure not to make careless mistakes.

TLDR:

Practise tutorials without ChatGPT Go through tutorial questions and answers, collate lecture slides into 1 document for easy ctrl-F-ing in the exams In the exams, aim to complete everything rather than perfect certain parts. Move on if you're stuck Don't be careless, read the questions carefully Work with trusted friends for the group project to minimise pain

Grades:

Expected grade: A- Actual grade: A

DSA2102

Module Coordinator & Lecturer: Dr Timothy Wertz

T/A: Tianyun

Lecture Topics:

Week 1: Introduction, Scientific Notation Week 2: Computer Arithmetic, Matrix Operations and Complexity Week 3: Systems of Linear Equations Week 4: Elimination with Pivoting, LU Factorization Week 5: Cholesky Factorization, Linear Least Squares Week 6: Gram-Schmidt Process, Reflections and Rotations Week 7: Singular Value Decomposition Week 8: Eigenvalue Problems Week 9: Power Iteration, QR Iteration Week 10: Singular Value Decomposition Revisited, Interpolation, Practical Interpolation Week 11: Orthogonal Polynomials Week 12: Numerical Integration Week 13: Error Formulas and Composite Quadrature, Other Integration Algorithms, Numerical Differentiation

Deliverables:

Homework - 5% x4 [lowest HW score can be substituted by lecture attendance grade] Midterm - 30% Finals - 50%

Other Comments:

This module is not difficult, but there's just a lot of content to remember. First of all, Dr Wertz is a pretty good lecturer, he is concise in explaining things and he splits his lectures into 3 categories: technical, conceptual, and enrichment. About 40% of the slides are enrichment which is nice to know but not required for the homework or exams. I would've liked to see a labelling of each slide under one of the 3 categories which would have made revising for exams a lot easier. Prof is also very helpful and answers questions at the end of the lecture. However, he also speaks very fast and tends to mumble/have run-off sentences so if your first language is not English, you might have a hard time understanding him.

There were 4 homeworks, each was out of 50. Like most math modules, the homework median is usually close to full marks, except for Homework 2 which had a killer counting operations of banded matrix question. As usual, discuss with friends to check your answers. The homework questions are mostly not tough, they are questions that are covered in lectures. Each homework also has an R coding question, but it's usually quite simple as prof has pseudocode in the slides, you just need to adapt them into actual code. If not, the tutorials also have an R question usually, refer to the tutorials for inspiration. Also, prof took lecture attendance, and while lectures are not compulsory (lectures are recorded too), it can replace your lowest homework grade, whichever is higher. I highly recommend getting the attendance grade as a safety net.

Tutorials were apparently hit-or-miss. My TA, Tianyun, was a pretty good TA and he explained relatively well. Sometimes, I didn't understand him but he was very approachable to me asking him questions after tutorial and he cleared all my doubts. He was also very dedicated, because there was one week that another TA took over him, and damn he kinda sucks because he doesn't explain well and totally skipped the R coding question, which I needed to solve a homework question. After asking the substitute TA about it, he just shrugged and said he doesn't provide R code. However, after I emailed Tianyun about it, he came up with his own R solution to the problem as prof hadn't sent him the solution yet. This sort of proactiveness is appreciated. As for the tutorial questions itself, it's mostly not hard and quite a good reflection of exam questions.

The midterm was a 80-minute pen-and-paper, scientific calculator exam, and we had to bring our own writing paper and scan our answers to upload ala homework-style within 10 minutes. The paper was relatively simple but computationally intensive, so avoid making careless mistakes. We were tested up to Week 6 content, and it was quite right-skewed. I got 41/50, the stats are 0 33 39 43 50. The final exam was a 2-hour pen-and-paper, scientific calculator exam that was out of 50. It was honestly even simpler than the midterm because it was less computationally-intensive, the first question was a bit odd, asking us to consider the number of operations to get the time complexity of some algorithms. The rest of the questions were standard, and mirrored questions from lecture examples, tutorials or the midterm/final practice papers that prof gave. Prof said he sets easier papers by not allowing us to bring cheatsheets in, and I think he kept to his word. The hard part comes in memorising the sheer number of algorithms and ways to solve the questions.

TLDR:

Keep up with tutorials so that you remember the algorithms more easily As usual, check homework answers with friends, attend lectures for safety net/grade boost in case you screw up a HW Try to understand the process of the algorithms to make life easier when studying for exams Don't make careless mistakes in exams

Grades:

Expected grade: B+ Actual grade: A

MA2311

Module Coordinator & Lecturer: Assoc Prof Leung Man Chun

T/A: Shixiao

Lecture Topics:

1. Sequences (Monotone convergence theorem, series, absolute and conditional convergence) 2. Tests of convergence (Power series and interval of convergence, Taylor’s series, differentiation and integration of power series) 3. Vectors in R2 and R3 (Dot product and cross product) 4. Functions of 2 or 3 Variables (Limits and continuity, partial derivatives, directional derivatives, gradients of functions, Taylor’s formula, maximum and minimum, second derivative test) 5. Vector-valued Functions of Several Variables (Chain rule, tangent planes and normal lines to surfaces in R3, Jacobians (change of volume/area element), Lagrange's multiplier method) 6. Multiple Integrals (Iterated integrals, change of order of integration, change of variable formula for multiple integrals)

Deliverables:

Midterms - 20% Finals - 80% (!!)

Other Comments:

Despite my grade for the mod, I can safely say this is the WORST mod I've taken in NUS so far. This prof really sucks, period. Although some math majors were warning ppl about him in the CHS group chat, I thought that since the module content was easy, even if the prof is bad it shouldn't be too big a problem. How wrong I was HAHA (but tbf, I heard Charmaine Sia who's teaching MA2104 isn't that great either and 2104 is tougher so it's not an easy choice). At this point, the module should be renamed to Techniques in Advanced Gambling because I felt like I was throwing a dart blindfolded and seeing what grade I would land. The 80% finals really made it feel like a lottery.

Let's start with the lectures. Someone else mentioned that the lecture slides were bad, and yes it's true. It's just emptiness all around, like very few words and some random diagrams and pictures. I can understand if the prof wants us to take notes, and that's why he left so many blanks. But the problem is that his lectures hardly refer to the slides. 99% of the time he's writing some stuff on paper and showing it to the lecture hall on the visualiser, so no one knows which part he's explaining, especially since he really cannot teach and explain things well to us. I think it's very hard to learn content from his lectures, but I do think there is some value in watching them which I will explain later. I managed to get my hands on the previous prof's lecture slides which helped me to keep up with the tutorials but I didn't watch the lectures from midterms until reading week, as a result, I didn't exactly master the later topics until reading week.

As for the tutorials, Shixiao was a pretty good TA because he would explain things in a way that made sense. He was also helpful despite a lot of dumb questions I asked at the end of each tutorial lol. He was probably the saving grace of this mod. However, the tutorial questions were directly ripped from last AY's MA2311 (this prof was the TA for the mod then) and the prof is so lazy that he didn't even remove the previous prof's name from the tutorial solution slides!! So this means no one really knows what kind of questions the prof will set since there's no reference or anything.

Midterms was a 1-hour pen-and-paper exam held in the lecture hall on Week 8, and it was open-book. Apparently, it was closed-internet but there was nothing to block internet access. Nonetheless, you have access to all your notes and I also downloaded Geogebra offline to check limits lol. We were tested until radius of convergence. 2 questions were directly from the tutorial but just slightly altered, the last question was slightly unorthodox but still doable. I got 19/20, and I think a lot of people did too. We only got back the midterms on the very last lecture in Week 13 so if you realised you screwed up there's honestly not much time to catch up. The average according to the prof was around 18/20.

Finals was your typical 2-hour, pen-and-paper, scientific calculator and 1 A4 double-sided cheatsheet math final exam. (Note: There was 1 part of question 1 that was voided and the paper was re-based to 95 instead of 100.) The fact that finals was 80% was extremely scary, and it was a sink-or-swim situation. I spent the bulk of reading week looking through the textbook and trying out questions from there (answers can be found online if you're resourceful enough), and alongside going through the prev AY's prof notes in more detail I got a better idea of the content. To be fair, most of the content was not difficult except for the part on volume multiple integration. Nonetheless, I still poured a lot of effort and time into this module because I couldn't risk the 80%. After understanding everything, I watched the prof's lectures to see if there was anything I missed out on and also to get some hints. He was emphasising one particular question at the end of the last week 13 lecture which I added wholesale into my cheatsheet, and lo and behold, it came out in the last question of the finals. As for the finals paper itself, I could do most of the questions, it was a relatively even spread across all the topics in both the first and second half but I wasn't sure if I got them correct because even the first question, which was a giveaway L-hopital limit question, I got wrong LOL. I think there were a few questions that felt a bit strange and unfamiliar, but if you know your concepts well it should not be an issue. Overall, some people felt it was easy and some felt it was difficult, which I attribute to whether you know the content and watched his lectures or not. Still though, 80% is crazyyyyyy

TLDR:

Listen to other ppl's advice, don't take this mod under this AY's prof unless you like gambling if you're taking it under him, I wish you all the very best

Grades:

Expected grade: idek Actual grade: A+