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The characteristics that set us apart
400+ Hours of
Instructor-Led Training
Dedicated Career Coach
150+ Hours of Self Paced Training
Professional Certification Program
500+ Exercises and Assesment
24/7 Support
The next Twelve months for you will look like this.
- Semester-I
- Introduction to Python and Data Science
- Working with Python Data Structures
- Control Flow Statements
- Functions in Python
- File Handling in Python
- Regular Expressions
- Object Oriented Programming
- Advanced-Data Structures in Python
- Introduction to SQL and MySQL
- Data Creation and Retrieval
- Data Filtering
- Data Analysis using aggregate functions and group by
- Joins and Keys
- MySQL Joins
- Subqueries and Views
- Window/Analytical Functions
- Case Study
- Introduction to Statistics
- Probability Theory
- Statistical Inference I
- Statistical Inference II
- Regression Analysis I
- Regression Analysis II
- Unleashing the Power of Excel
- Data Analysis with MS Excel
- Summarizing and Forecasting
- Macros and Dashboarding
- Excel Project Session
- Semester-II
- Extracting and Aggregating Pandas
- Matplotlib and Seaborn
- Plotly and Cuffinks
- Introduction to Data Cleaning and Data Types
- Exploring and Visualization the missing values
- Advanced-Data Cleaning Concepts
- Introduction to Feature Engineering
- Feature Extraction and Transformation
- Feature Selection and Dimensionality Reduction
- Modeling with Linear Regression
- Evaluating Models & Feature selection
- Regularisation Techniques
- Modeling with Logisitc Regression
- Understanding other classification
algorithm like KNN & SVM - Advanced Model Evaluation Techniques
- Introduction to Clustering and K Means
- Advanced Clustering Techniques
- Semester-III
- Introduction to Decision Trees
- Implementation of Decision Trees
- Introduction to the Concept of Bagging
- Introduction to Concept of Random Forest
- Introduction to Boosting
- Introduction to extreme Gradient Boosting
- Introduction to Imbalanced Machine Learning models
- Introduction to Recommendation Engines
- Introduction to Time Series Analysis
- Preprocessing and Visualization of Time Series Data
- Time Series Forecasting using ARIMA
- Exponential Smoothing Models for Time Series Forecasting
- Machine Learning Models for Time Series Forecasting
- Time Series Forecasting using Prophet
- NLP Fundamentals
- Feature Engineering in NLP & Text Classification
- Advanced-Data Cleaning for NLP text classification
- Feature Extraction & Feature encoding for NLP
- Introduction to Word Embeddings
- Advanced word embeddings used to solve NLP problems
- More about advanced NLP
- NLP text classification end to end project from kaggle
- Building blocks of Deep Learning
- Understanding the Components of a Neural Network
- Introduction to Recurrent Neural Networks
- Overview of LSTM and GRU
- Introduction to Bidirectional Networks
- RNN Use Cases in the Industry
- Introduction to Convolutional Neural Networks (CNN)
- Overview of Transfer Learning
- Introduction to Transformers
- Overview of AutoEncoders
- Internship Program
This internship is a part of the course curriculum to help you gain real experience in the Data Science domain.During this internship, you will go through various challenges which you allow to explore new skills and push your limits while learning something new during the projects.
- Soft Skills Program
Technical skillset and your soft skills combine to make you employable. In order to make our learners employable, dedicatedly placement-oriented sessions are conducted while highlighting the use of Github, Linkedin, and other tools during the job search.
- Placement
Plans & Pricing
Data Science Training & 360° Placement Assistance
360° Placement Assistance
We guide you to get into the best companies
50+ Career Specialists
We help you throughout you career journey
13000+ Students : 1200+ Career Partners
This Healthy ratio ensures every student gets into a good company from Dataisgood
Our Team of Experts
Don Joe Jacob
Big Datā & BI Specialist
Joe Jacob has more than 5 years of working in the Education Field. He is the Machine Learning Lab Head, and Chief Content Creator at Dataisgood. He is a renowned expert in Machine Learning and Optimization, Document Image Analysis, and Computer Vision.
Chandan Sen Gupta
Data Science & Machine Learning Specialist
Chandan holds a PG Diploma in Computer Programming. He is an Industry Instructor, Instructional Designer, and Programming Guru, with a software development experience of over 35 years. His subject-matter expertise includes Programming languages – COBOL, Cl ipper, C, C++, Python, Haskel l, El ixir, Clojure, Java and Ruby.
Arpit Sharma
Data Scientist & Machine Learning Specialist
Data scientist with hands-on experience in machine learning model creation, optimization, NLP, timeseries analysis, forecasting, and computer vision. Passionate about exploring new dimensions in data science. Having an aim to connect thousand’s of aspiring minds with the Metaverse of Analytics and Artificial Intelligence Domain.
Frequently Asked Questions
For your capstone project, you’ll tackle a real-world data problem from end to end. Develop a pitch and problem statement, source and collect relevant data, conduct an exploratory data analysis, and build a predictive model.
You’ll document and share your findings through a presentation, technical report, and non-technical summary. Throughout this Accelerator Course you’ll also compile a portfolio of projects designed to reinforce what you’ve learned in each unit.
Yes, Of Course.
You will get Assistance from our Teaching Assistants any time you wish.
The Teaching Assistants will help you to complete the Capstone Project if you face any difficulties. Apart from that our Mentors and Instructors will also help you to Come up with New and amazing ideas for the Capstone Project.
You will get access to unlimited doubt resolution sessions any time as per your convenience. We have a team of highly skilled subject matter experts who are available through out the course duration to help you. You can request for doubt resolution session directly through out WhatsApp communication channel.
This programme is designed for students looking to start career into the data domain. Considering the requirements of different data roles in the industry, the curriculum is divided into two tracks. The track will run for the first 5-6 months that where you will get to learn Basics of SQL, Python, Statistics and EDA. In the second track you will get to learn more advanced content such as Basic Machine Learning Models, Advanced Machine Learning, Neural Networks, Advanced Machine Learning, Natural Language Processing, Building Data Pipelines, Data Streaming and AutoML.
You will require to dedicate atleast 12-15 hours per week to fully learn and understand the basic concepts covered during the course. This much time commitment is expected to be able to achieve complete learning outcomes offered from the programme.
The content will be a mix of interactive lectures from industry leaders as well as Expert faculties. Additionally, the programme comprises of live lectures, Ebooks, Study Notes, Self Learning Materials, Practice Datasets and Projects which will enhance your learning experience. Case studies and group projects will also facilitate peer-to-peer interactions.
Yes, Of course.
Additionally you will also get a certificate for the completion of your Capstone Project towards the end of the Programme.