In our current world where data rules, having data science skills is essential rather than just a nice-to-have. The need for data experts is on the rise, and those with the right skills are in high demand. However, learning these skills can often come with a hefty price tag and take a lot of time. Luckily, IBM is making data science education more accessible by offering a variety of free certification courses. This initiative allows aspiring data scientists from diverse backgrounds to gain important knowledge, enhance their portfolios, and kickstart their careers in this dynamic field. This article will dive into the specifics of these free IBM data science certifications, covering the curriculum, benefits, and how you can jump in today.
1. Python for Data Science, AI & Development– Click here
What you’ll learn
- Learn Python
- Apply Python programming logic Variables, Data Structures, Branching, Loops, Functions, Objects & Classes.
- Demonstrate proficiency in using Python libraries such as Pandas & Numpy, and developing code using Jupyter Notebooks.
2. IBM Cybersecurity Analyst Professional Certificate – Click here
What you’ll learn
- You need to get an entry-level position as a cybersecurity analyst in just 4-6 months.
- Cybersecurity fundamentals and how to manage database vulnerabilities in operating systems administration and security
- use cybersecurity tools and techniques to perform penetration testing, respond to incidents, and conduct forensics.
3. IBM Data Science Professional Certificate –Click here
What you’ll learn
- Master the most up-to-date practical skills
- Learn the tools, languages, and libraries used by professional data scientists, including Python and SQL
- Import and clean data sets, analyze and visualize data, and build machine learning models and pipelines
4. Machine Learning with Python – Click here
What you’ll learn
- UtilizeScikit-learn to build, test, and evaluate models.
- Data preparation techniques and manage bias-variance tradeoffs to optimize model performance.
- Implement core machine learning algorithms, including linear regression, decision trees, and SVM, for classification and regression tasks.
5.What is Data Science? – Click here–
What you’ll learn
- Define data science and its importance in today’s data-driven world.
- Summarize advice given by seasoned data science professionals to data scientists who are just starting out.
- Describe the various paths that can lead to a career in data science.
6. IBM Introduction to Machine Learning Specialization – Click here
What you’ll learn
- Understand the potential applications of machine learning
- Identify opportunities to leverage machine learning in your organization or career
- Communicate findings from your machine learning projects to experts and non-experts
- Gain technical skills like SQL, machine learning modelling, supervised and unsupervised learning, regression, and classification.
7. IBM Machine Learning Professional Certificate – Click here
What you’ll learn
- Master the most up-to-date practical skills and knowledge machine learning experts use in their daily roles
- Learn how to compare and contrast different machine learning algorithms by creating recommender systems in Python
- Develop working knowledge of KNN, PCA, and non-negative matrix collaborative filtering
