IBM Python for Data Science, AI & Development

Best value

Free!

Certificate

Earn a career certificate

Level

Intermediate

Duration

26 Hours

Kickstart your learning of Python with this beginner-friendly self-paced course taught by an expert. Python is one of the most popular languages in the programming and data science world and demand for individuals who have the ability to apply Python has never been higher.

(2 customer reviews)
Product is rated as #3 in category AI Coding
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You will get: Describe Python Basics including Data Types, Expressions, Variables, and Data Structures. Demonstrate proficiency in using Python libraries such as Pandas, Numpy, and Beautiful Soup. Apply Python programming logic using Branching, Loops, Functions, Objects & Classes. Access web data using APIs and web scraping from Python in Jupyter Notebooks.
  • Aspiring AI Developers and Engineers: Ideal for those aiming to enter the AI field with a strong focus on practical application and coding.
  • Professionals with a Basic Understanding of Programming: Best suited for individuals who already have some programming experience and are looking to specialize in AI.
  • Learners Interested in Hands-On Projects: Great for those who prefer learning through doing, with numerous opportunities to build AI solutions for real-world scenarios.
  • Data Scientists Looking to Diversify Their Skills: Beneficial for data professionals wanting to expand into AI-specific applications and techniques.
  • Hobbyists with an Interest in AI and Game Development: A good choice for enthusiasts interested in exploring AI through games and interactive projects.
  • Continuing Education for IT Professionals: Useful for IT professionals seeking to update their skills in line with current AI trends and technologies.
  • Complete Beginners in Programming and AI: The course’s complexity and prerequisite of programming knowledge make it less suitable for absolute beginners.
  • Learners Seeking Formal University Accreditation: Since the course doesn’t provide detailed information about formal accreditation, it might not meet the needs of those seeking recognized academic qualifications.
  • Individuals Looking for a Light, Introductory Course: The course’s depth and length might be overwhelming for those seeking a more casual or introductory learning experience.

8Expert Score
Great introduction course to Python for AI

This course is well-suited for beginners and intermediate learners in Python, data science, and AI. It offers a good mix of theoretical knowledge and practical application, taught by a reputable institution. The course is flexible, affordable, and provides a solid foundation in Python for data science and AI.

Course Content and Structure
8
Instructor Expertise and Teaching Approach
7
Practical Application and Hands-On Learning
9
Learning Outcomes and Skill Development
8
The Credibility of the Platform and the Institution
6
Duration and Time-Flexibility
9
Interaction and Engagement
7
Cost and Value for Money
8
Student Feedback and Success Stories
7
Overall Recommendation
8
PROS
  • Comprehensive Curriculum: Covers a wide range of topics from basic Python programming to advanced applications in data science and AI.
  • Practical Focus: Includes hands-on projects and case studies, enhancing real-world skills.
  • Industry-Relevant Tools: Teaches important tools like Pandas, NumPy, and SQL, crucial for data science.
CONS
  • Potentially Basic for Advanced Learners: May not offer sufficient depth for those already experienced in Python or data science.

Kickstart your learning of Python with this beginner-friendly self-paced course taught by an expert. Python is one of the most popular languages in the programming and data science world and demand for individuals who have the ability to apply Python has never been higher.

This introduction to Python course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn about Python basics and the different data types. You will familiarize yourself with Python Data structures like List and Tuples, as well as logic concepts like conditions and branching. You will use Python libraries such as Pandas, Numpy & Beautiful Soup. You’ll also use Python to perform tasks such as data collection and web scraping with APIs.

You will practice and apply what you learn through hands-on labs using Jupyter Notebooks. By the end of this course, you’ll feel comfortable creating basic programs, working with data, and automating real-world tasks using Python.

This course is suitable for anyone who wants to learn Data Science, Data Analytics, Software Development, Data Engineering, AI, and DevOps as well as a number of other job roles.

Full Aiology Review

1. Course Content and Structure – 8/10

  • Relevance and Coverage: The course offers a comprehensive introduction to Python with a focus on data science, AI, and development. It covers basic programming concepts, data types, conditions, loops, functions, and file handling, along with advanced topics like APIs, web scraping, and data manipulation with Pandas and NumPy.
  • Depth and Complexity: The content progresses from basic to more complex topics, suitable for beginners and intermediate learners. However, advanced users might find some sections basic.
  • Rating: 8/10 – Excellent coverage for beginners and intermediate users, but may lack depth for advanced learners.

2. Instructor Expertise and Teaching Approach – 7/10

  • Instructor Credentials: Detailed information about the instructor’s background is not provided in the document. More research is needed to evaluate their expertise.
  • Teaching Style: The course seems to be well-structured with a focus on practical applications. It gradually introduces complex topics, making it accessible for beginners.
  • Rating: 7/10

3. Practical Application and Hands-On Learning – 9/10

  • Project Work and Case Studies: The course includes practical projects like creating a Plotly dashboard and working with SQL databases, offering hands-on experience.
  • Tools and Technologies: Teaches relevant tools such as Python, Pandas, NumPy, SQL, and Plotly, which are crucial in the field of data science and AI.
  • Rating: 9/10 – Strong practical component and relevant tool usage.

4. Learning Outcomes and Skill Development – 8/10

  • Skill Acquisition: Students will gain foundational skills in Python programming, data analysis, and machine learning concepts.
  • Career Relevance: The course is relevant for roles in data science, AI, and software development.
  • Certification and Accreditation: The course offers a certificate, but its industry recognition is limited.
  • Rating: 8/10 – Good for skill development

5. The Credibility of the Platform and the Institution – 6/10

  • Platform/Institution Reputation: Offered on Coursera by IBM, which has a strong reputation in the tech industry.
  • Accreditations and Affiliations: IBM is a well-known entity, but specific accreditations for this course are not mentioned.
  • Specialization and Expertise: IBM’s expertise in AI and data science adds value to the course.
  • Rating: 9/10 – Reputable platform and provider

6. Duration and Time-Flexibility – 9/10

  • Course Length: Approximately 5-6 months, but can be completed faster depending on the learner’s pace.
  • Time Flexibility: Self-paced, suitable for learners with varying time commitments.
  • Course Format: Online and self-paced, allowing flexibility.
  • Rating: 9/10 – Highly flexible and suitable for different learners.

7. Interaction and Engagement – 7/10

  • Interactive: Provides interactive labs and projects.
  • Community Engagement: Community engagement is not explicitly mentioned.
  • Rating: 7/10 – Interactive content is strong, but community aspects are unclear.
  •  

8. Cost and Value for Money – 8/10

  • Pricing Structure: $39 per month on Coursera.
  • Value Assessment: Considering the comprehensive content and practical projects, the course offers good value for money.
  • Rating: 8/10 – Reasonably priced for the content and skills offered.

9. Student Feedback and Success Stories – 7/10

  • Reviews and Ratings: The reviews are generally positive, with students appreciating the practical aspects and comprehensive content.
  • Rating: 7/10 – Positive reviews, but more detailed success stories would be beneficial.

10. Overall Recommendation – 8/10

  • Final Verdict: This course is well-suited for beginners and intermediate learners in Python, data science, and AI. It offers a good mix of theoretical knowledge and practical application, taught by a reputable institution. The course is flexible, affordable, and provides a solid foundation in Python for data science and AI.
  • Overall Rating: 8/10 – Highly recommended for its comprehensive content, practical focus, and flexible learning structure.

2 reviews for IBM Python for Data Science, AI & Development

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  1. Jax

    Like the other parts of the certificate, the tasks are just too simple. The content in the videos (with many typos!!) is quite valuable, but the tasks, oh man… They only skim the surface, never diving deep into the details. This course introduces libraries like numpy and pandas, but surprisingly, we didn’t even need them for the final assignment. I was excited reading the final assignment’s description, expecting to code everything from scratch – really getting into the nitty-gritty, testing in a notebook, reading documentation, and discovering cool stuff. But, sadly, that didn’t happen. The most challenging function was already provided, and some answers felt more like copy-pasting than applying what we learned. I was leaning towards giving 4 out of 5 stars, but after reflecting in this review, I’m down to just 3 stars. And that feels a bit harsh because it’s clear a lot of effort and passion went into the course content. It’s just a shame so much potential wasn’t fully utilized.

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  2. Ceci m

    As a true beginner to programming, I had high hopes for this course but ultimately felt it did not provide the foundation I needed. The introductory videos and exercises in the first two weeks gave me fascinating initial insights into Python and I really appreciated the clear explanations in the lectures. However, as the course progressed the hands-on activities became extremely challenging. By Week 3, I was mostly just running pre-written code instead of building skills to write my own programs.

    For genuinely new programmers, there is a steep learning curve here. Topics like web scraping and lists are briefly shown rather than thoroughly taught. While intermediate or advanced coders would likely breeze through, beginners may find the pace too fast and the exercises too difficult without more coding preparation first.

    I think this course has a lot to offer the right audience in terms of interesting applications, butadditional prerequisites or beginner-focused material is needed. The emphasis seems more on showing what Python can do versus developing true coding proficiency from the ground up. If you are familiar with Python or other languages already, you will probably find the content straight-forward. As a true first-timer, I grew quickly frustrated by my inability to actively code on my own.

    For true coding beginners, I would not recommend this as an introductory course. Start first with more basic Python programming prep before tackling these advanced exercises. Gain some hands-on practice with core concepts like variables, loops, and functions to build your skill level – otherwise this course may prove discouraging rather than properly educational for individuals like myself.

    + PROS: Interesting applications shown for Python programming Well-made intro videos explain concepts clearly First couple weeks provide good initial insights
    - CONS: Too advanced for true beginners Steep learning curve once gets into more complex coding Lack of focus on building programming fundamentals Exercises quickly become extremely difficult Not enough practice writing own code from scratch More prep needed for beginners to handle pace and difficulty
    Helpful(0) Unhelpful(0)You have already voted this

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    IBM Python for Data Science, AI & Development
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