Data Science and AI Certification Course

Prepare youself for the in-demand roles in the industry. Launch your career in Data Science & AI.Earn ₹ 6-18 LPA at leading companies

Pay Course Fee After Placements.

Live Online classes.

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Highlights of the program

  • Recorded lectures available
  • Live projects
  • 1:1 Mentorship
  • Doubt solving
  • Course duration: 9 months

Course details: Modules in the certification program

Part A

  • Introduction to Programming Concepts
  • Variables, Data Types, and Operators
  • Control Structures and Loops
  • Functions and Modular Programming
  • File Handling and Input/Output Operations
  • Error Handling and Exception Handling
  • Introduction to Algorithms and Data Structures

  • Data Wrangling and Preprocessing
  • Exploratory Data Analysis
  • Data Visualization with Matplotlib and Seaborn
  • Data Cleaning and Transformation Techniques
  • Data Aggregation and Group Operations
  • Statistical Analysis and Hypothesis Testing
  • Dimensionality Reduction Techniques
  • Risk Identification and Assessment
  • Feature Engineering and Selection

  • Introduction to Relational Databases
  • SQL Fundamentals and Data Manipulation
  • Database Design and Normalization
  • Advanced SQL Queries and Joins
  • Subqueries and Nested Queries
  • Indexing and Query Optimization
  • Stored Procedures and Triggers
  • Stakeholder Engagement and Management
  • Database Administration and Security

  • Introduction to Probability Theory
  • Random Variables and Probability Distributions
  • Descriptive Statistics and Data Summarization
  • Sampling Techniques and Estimation
  • Hypothesis Testing and Inference
  • Analysis of Variance (ANOVA)
  • Regression Analysis and Model Building
  • Nonparametric Methods and Survival Analysis

  • Introduction to Machine Learning and its Applications
  • Supervised Learning: Regression and Classification
  • Model Evaluation and Validation Techniques
  • Decision Trees and Ensemble Methods
  • Support Vector Machines (SVM)
  • Naive Bayes and K-Nearest Neighbors (KNN)
  • Unsupervised Learning: Clustering and Dimensionality Reduction
  • Introduction to Deep Learning and Neural Networks

  • Introduction to Natural Language Processing (NLP)
  • Text Preprocessing and Tokenization
  • Text Representation and Feature Extraction
  • Sentiment Analysis and Text Classification
  • Named Entity Recognition and Part-of-Speech Tagging
  • Topic Modeling and Latent Dirichlet Allocation (LDA)
  • Word Embeddings and Language Models
  • Neural Machine Translation and Text Generation

    • Part B

  • Introduction to Time Series Analysis
  • Time Series Visualization and Decomposition
  • Stationarity and Time Series Models
  • Autoregressive Integrated Moving Average (ARIMA)
  • Exponential Smoothing Methods
  • Seasonal and Trend Decomposition using Loess (STL)
  • Forecast Evaluation and Accuracy Measures
  • Advanced Forecasting Techniques and Model Selection

  • Neural Network Architecture and Activation Functions
  • Convolutional Neural Networks (CNN)
  • Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM)
  • Generative Adversarial Networks (GAN)
  • Transfer Learning and Fine-Tuning
  • Reinforcement Learning and Deep Q-Networks (DQN)
  • Natural Language Processing with Deep Learning
  • Explainable AI and Interpretability Techniques

  • Introduction to Big Data and Hadoop
  • Distributed File Systems (HDFS)
  • MapReduce and Apache Spark
  • Data Streaming and Real-time Processing
  • Data Extraction, Transformation, and Loading (ETL)
  • NoSQL Databases and Document Stores
  • Distributed Machine Learning with Spark
  • Scalable Data Visualization and Dashboards

  • Recommendation Systems
  • Anomaly Detection
  • Ensemble Learning and Stacking
  • Reinforcement Learning Applications
  • Deep Reinforcement Learning
  • Time Series Deep Learning Models
  • Automated Machine Learning (AutoML)
  • Model Deployment

    • Course Features

    Hands-on Projects

    Put your skills into practice with real-world projects designed to simulate industry scenarios. Gain practical experience and develop a portfolio to showcase your abilities to potential employers.

    Expert Instructors

    Learn from experienced professionals in the digital marketing and front-end development fields. Our instructors bring their industry expertise and provide valuable insights and guidance throughout the course.


    Interactive Learning

    Engage in interactive learning experiences, including live sessions, group discussions, and collaborative projects. Benefit from the support and interaction with fellow learners, fostering a dynamic learning community.

    Career Support

    Receive career guidance, resume review, and interview preparation to enhance your job prospects. Take advantage of networking opportunities and access our network of industry connections to explore job placement possibilities.


    Course Instructor

    Alekh Shekhar|Senior Data Scientist @IBM|Ex-Accenture

    10+ Years of Industry Experience

    Alekh is a seasoned data science professional,
    with extensive expertise and a passion for mentoring aspiring data scientists.
    He has 10+ years of industry experience,
    dedicated to helping individuals develop their skills and thrive in the field of data science.

    LinkedIn Profile: Alekh Shekhar

    Portfolio Rating: ★★★★★

    Final words

    Enroll in our Digital Marketing & Front End Course today and unlock your potential in these high-demand fields. Whether you're looking to launch a new career, upskill, or enhance your business's online presence, this course is your stepping stone to success.

    Join us now and embark on an exciting learning journey that will empower you with the skills and knowledge to thrive in the digital world!