With new capstone projects, learn how to apply your previous domain expertise to make a successful transition.
Data Science and AI Program | Advance
Choose Specialization over Generalization
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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
5/5
Arjun Kumar
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.
5/5
John Doe
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.
Premium Mentoring
Get professionally trained from MAANG and MNC experts
Crafted for professional
Prioritize growth and salary hike with in-demand skillset
5/5
Daksh Mishra
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.
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.
Highlight your profile and get recognition from renowned industries worldwide. Work on latest capstones and achieve a project experience certificate from IBM.
Expert Data Science & AI Program : Batch Details
New batches start 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
- MongoDB (Advance)
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
Module 5 :- Big Data & Spark Analytics
- Introduction To Hadoop & Big Data
- What is Spark
- Getting to know PySpark
- Hands-on: Map reduce Use Case : Youtube data analysis & Spark RDD programming
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
Module 8 :- Dashboard & Stories with Macros
Module 1 :- Deep Learning Using Tensorflow
- Introduction to Deep Learning And TensorFlow
- TensorFlow Classification Examples
- Understanding Neural Networks With TensorFlow
- Convolutional Neural Network (CNN)
- Project on Building a CNN for Image Classification
Module 2 :- Natural Language Processing (NLP)
- Natural Language Processing
- Text Analysis
- KNN
- Use cases on NLP: Sentiment analysis for marketing
Module 3 :- Model Training & Deployment Using (AWS GCP)
- AWS (Amazon Web Services)
- GCP (Google Cloud Platform)
- Introduction to AWS and GCP Cloud ML Engine
- Deploying Machine Learning Model
- Introduction to Azure Machine Learning
- Deploying Machine Learning Models using Azure
- Training Machine Learning Model
Module 4 :- ChatGPT
- Understanding of ChatGPT powered by LLM (Large Language Model)
- Pro-tips on prompt design and ChatGPT usage
- Explore ChatGPT, GPT-4, Dalle-2
- Create code and apps using the open API of OpenAI
- Potential Use Cases For ChatGPT
- Virtual customer care representatives
- Personal assistants
- Social media moderation
- Language translation
Module 5 :- Introduction to MLOps
- MLOps lifecycle
- MLOps pipeline
- MLOps Components, Processes, etc
Stand a chance to pitch for an investment to Industry Experts for your own AI products
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Program Features
- Job Assistance
- Live Class Subscription
- LMS Subscription
- Job Referrals
- Industry Projects
- Capstone Projects
- Domain Training
- Project Certification from Companies
Basic
₹ 29900+ GST
- ☑
- 1 Years
- Lifetime
- 3+
- 7+
- 1
- X
- X
Advance
₹ 49900+ GST
- ☑
- 3 Years
- Lifetime
- 5+
- 15+
- 3
- ☑
- ☑
Expert
₹ 79900+ GST
- ☑
- 3 Years
- Lifetime
- Unlimited
- 20+
- 5
- ☑
- ☑