IBM Data Science Professional Certificate

Professional Certificate - 10 Course Series

Prepare for a career in the high-growth field of data science. In this program, you’ll develop the skills, tools, and portfolio to have a competitive edge in the job market as an entry-level data scientist in as little as 5 months. No prior knowledge of computer science or programming languages is required. Data science involves gathering, cleaning, organizing, and analyzing data with the goal of extracting helpful insights and predicting expected outcomes. The demand for skilled data scientists who can use data to tell compelling stories to inform business decisions has never been greater. You’ll learn in-demand skills used by professional data scientists including databases, data visualization, statistical analysis, predictive modeling, machine learning algorithms, and data mining. You’ll also work with the latest languages, tools,and libraries including Python, SQL, Jupyter notebooks, Github, Rstudio, Pandas, Numpy, ScikitLearn, Matplotlib, and more.
Upon completing the full program, you will have built a portfolio of data science projects to provide you with the confidence to excel in your interviews. You will also receive access to join IBM’s Talent Network where you’ll see job opportunities as soon as they are posted, recommendations matched to your skills and interests, and tips and tricks to help you stand apart from the crowd. This program is ACE® recommended—when you complete, you can earn up to 12 college credits.


Applied Learning Project This Professional Certificate has a strong emphasis on applied learning and includes a series of hands-on labs in the IBM Cloud that give you practical skills with applicability to real jobs. Tools you’ll use: Jupyter / JupyterLab, GitHub, R Studio, and Watson Studio
Libraries you’ll use: Pandas, NumPy, Matplotlib, Seaborn, Folium, ipython-sql, Scikit-learn, ScipPy, etc. Projects you’ll complete:

Foundations: Data, Data, Everywhere

Course-1

Ask Questions to Make Data-Driven Decisions

Course-2

Prepare Data for Exploration

Course-3

Process Data from Dirty to Clean

Course-4

Analyze Data to Answer Questions

Course-5

Share Data Through the Art of Visualization

Course-6

Data Analysis with R Programming

Course-7

Google Data Analytics Capstone: Complete a Case Study

Course-8