I had a great learning experience at Wikipidia Academy. The faculties here are top-notch. Right from enrollment to getting a good job, they keep putting enormous efforts into each and every candidate. Thanks to all the trainers, the backend team, the HR team and the directors for making this journey smooth.
Data Science and AI Program | Basic
Duration: 6 Months
Choose Specialization over Generalization
With new capstone projects, learn how to apply your previous domain expertise to make a successful transition.
Global Recognition
From IBM
Industry Standard
Training
Career Assistance
For Professionals
Financing as low as
Why Enroll In This Program?
1-on-1 Dedication
Live interactive session with expert for every individual
Assured Interview Call
Get job referrals powered by 250+ hiring partners
Premium Mentoring
Get professionally trained from MAANG and MNC experts
Designed for Beginners
Start your career in Data Science with good salary
Thanks to the Wikipidia Academy’s data science course and outstanding assistance, I could ace the TCS interview and secure a job with a 400% pay hike. My understanding of the course was greatly improved by the real-time projects and respective IBM project experience certification.
I always had a dilemma about how to switch to the IT field until I stumbled upon the foundation data science course offered by Wikipidia Academy. The perfect combination of flexibility, affordability, and supportiveness. They helped me get placed at Capgemini, and I’m delighted with my current career.
What Makes Us Different?
You have several options when choosing any course from Wikipidia as we have never failed our promises.
Take advantage of interactive, live learning in comfort of your home. Experts from MNCs and MAANG assist in online and offline project sessions at different project innovation centers around 7+ cities in India.
Get the advantage of experienced candidate to make the most out of it. Make a switch as a professional, not as a fresher by utilizing your existing knowledge through domain specialization.
Highlight your profile and get recognition from renowned industries worldwide. Work on latest capstones and achieve a project experience certificate from IBM.
Enjoy 1 year of limitless independence for accessing all the learning materials, live batches, and project sessions. Make your learning calendar as per your convenience. Professionals get to switch between weekdays and weekends.
Basic Data Science & AI Program : Batch Details
New batches starts on 5th, 15th & 25th of every month.
Syllabus
Wikipidia provides Live, Interactive Online Sessions guided by Professionals working in top MNCs. All sessions are covered practically with real-time industrial projects and case studies.
Topic 1 :- Cohort Orientation
- A brief introduction to tools related to data
- Learn about particular real-time projects and Capstone projects
- Data and its impact on career opportunities
- Utilizing data, to enhance industrial operations and management
Topic 2 :- Fundamentals of Programming
- Introduction to Anaconda & Jupyter notebook
- Flavors of python Introduction to Git, GitHub
- Python Fundamentals
Topic 3 :- Fundamentals of Statistics
- Mean, Median, Mode
- Standard Deviation, Average. Probability, Permutations, and Combinations
- Introduction to Linear Algebra
Module 1 :- Python Programming
- Programming Basics & Environment Setup
- Python Programming Overview
- Strings, Decisions & Loop Control
- Python Data Types
- Functions And Modules
- Class hands-on: 8+ Programs to be covered in the functions, Lambda, modules, Generators, and Packages class
- File I/O And Exceptional Handling and Regular Expression
- Class hands-on: 10+ Programs to be covered in class from File IO, Reg-ex and exception handling
- Data Analysis Using Numpy
- Data Analysis Using Pandas
- Data Visualization using Matplotlib
- Data Visualization using Seaborn
- Case Study on Numpy, Pandas, Matplotlib 1 Case Study on Pandas And Seaborn
Module 1 :- Statistics
- Fundamentals of Math and Probability
- All about Population & Sample
- Introduction to Statistics, Statistical Thinking
- Descriptive Statistics
- Inferential Statistics
- Hypothesis Testing
- Linear Algebra
- Data Processing & Exploratory Data Analysis
- EDA
- Statistics Assignments: Total 4 practice sets and Assignments from Statistics
Module 2 :- Machine Learning
- Introduction to Machine Learning
- Regression and Classification Models
- Linear Regression Model
- Data Preprocessing
- Encoding the Data
- Logistic Regression Model
- Evaluation Metrics for Classification model
- K Nearest Neighbours Model
- Decision Tree Model
- Random Forest Model
- Hyperparameter Tuning
- Naive Baye’s Model
- Case Study on Kart Model Business & Random Forest
- K Means and Hierarchical Clustering
- Hierarchical Clustering
- Principal Component Analysis (PCA):
- Support Vector Machine(SVM)
Module 1 :- SQL
- SQL and RDBMS
- Advance SQL
- NoSQL, HBase & MongoDB
- JSON Data & CRUD
- Programming with SQL
Module 2 :- MongoDB
- Introduction to MongoDB
Module 3 :- Tableau
- Introduction to Tableau
- Visual Analytics
- Dashboard and Stories
- Hands-on: Connecting data source and data cleansing
- Working with various charts, Deployment of Predictive model in visualization
Module 4 :- PowerBI
- Getting Started With Power BI
- Programming with Power BI
- Dashboard and Stories
- Hands on: Power BI Projects
- Table Navigation
- Matrix Navigation
- Pane Navigation
- Canvas Zoom/Slicer/Selection Pane
- DAX Formula Bar
Module 5 :- Basics of Big Data & Spark Analytics
- Introduction To Hadoop & Big Data
- What is Spark
- Getting to know PySpark
Module 6 :- Time Series
- Introduction to Time Series Forecasting
- Introduction to ARIMA Models
- Case Study on Time series classification of smartphone data to predict user behavior, Performing Time Series Analysis on Stock Prices & Time series forecasting of sales data
Module 1 :- MS Excel Fundamentals
Module 2 :- Worksheet Customization
Module 3 :- Working with Images & Shapes in Excel Worksheet
Module 4 :- Basic MS Excel
Module 5 :- Advance Excel Formula
Module 6 :- Advance Excel Functions
Module 7 :- Charts & Graphs
Module 8 :- Dashboard & Stories with Macros
- Job Assistance
- Live Class Subscription
- LMS Subscription
- Job Referrals
- Industry Projects
- Capstone Projects
- Domain Training
- Project Certification from Companies
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Data science is accessible to everyone, regardless of prior experience. All you need is an interest in working with data and some basic computer skills. If you already have a basic understanding of statistics and coding, you might even be able to skip introductory courses.
Learn More – How to become a Data Scientist?
Starting a data science career can be fulfilling, especially for analytical minds who thrive on coding and data manipulation. As a data scientist, you’ll delve into various programming languages, navigate data systems, and extract insights to solve real-world problems. Effective communication is crucial since you’ll collaborate with teams to deliver findings. Moreover, data science serves as a strong base for machine learning and AI—an ever-expanding field. In just a few months, you can acquire data science skills applicable across diverse industries.
Still not sure? Book a Free Counselling Session Now!
Data science encompasses various roles, including data scientists, data analysts, data architects, and data engineers. Proficiency in data science skills is valuable for business and marketing analysts who rely on system tools to extract and analyze data. Given its widespread demand, data science finds applications across nearly every industry.
Learn More: Data Science – The Finest Job of 21st Century
Recently, there has been a significant increase in demand for online courses. Pursuing a master’s degree in data science can lead to progressive career growth. Online courses are particularly beneficial for working professionals who seek to learn data science without compromising their schedules.