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Professional Certification Course in Data Science with Machine Learning

100% Job Assurance in Professional Certification Course in Data Science with Machine Learning

Learn from global experts and get certified by Digicrome

Suitable for Final Years, Graduates and Early Professionals

You`re guaranteed to find something that`s right for you.

What Our Program Offers?

Discover the key features and benefits you'll gain from joining our program

Master Machine Learning Master Machine Learning
Data Science Fundamentals Data Science Fundamentals
Real-World Projects Real-World Projects
Hands-on Training Hands-on Training
Interactive Live Sessions Interactive Live Sessions
Python Programming Skills Python Programming Skills
Supervised Learning Models Supervised Learning Models
Unsupervised Learning Techniques Unsupervised Learning Techniques
Industry-Grade Curriculum Industry-Grade Curriculum
Data Visualization Tools Data Visualization Tools
Expert Mentorship Support Expert Mentorship Support
Capstone Project Inclusion Capstone Project Inclusion
End-to-End Training End-to-End Training
Career-Oriented Approach Career-Oriented Approach
Interview Preparation Assistance Interview Preparation Assistance
Certification Upon Completion Certification Upon Completion
AI Integration Basics AI Integration Basics
Tools and Frameworks Tools and Frameworks
Resume Building Guidance Resume Building Guidance
Self-Paced Flexibility Self-Paced Flexibility

Trusted by world's best Organisations

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About the Program

Our Professional Certification Course in Data Science with Machine Learning will prepare you with the in-demand skills to revolutionize raw data into actionable visions and build intelligent solutions, although your background. This intensive certification takes you from foundational data handling and statistical analysis to advanced machine learning algorithms. You'll gain hands-on proficiency with various industry-standard tools and techniques, containing Python, SQL, data visualization, predictive modeling, and deep learning, through practical projects and under the direction of experienced masters. This program is created to supply job-ready skills, enabling you to excel in data-compelled roles across diverse industries.

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Course Overview

In today’s rapidly advancing technological landscape, data science and machine learning have become crucial fields that drive innovation and deliver valuable insights across industries. The Professional Certification Course in Data Science with Machine Learning is meticulously designed for professionals and enthusiasts in the USA, equipping them with the expertise needed to excel in this transformative domain.

 

Why Choose a Professional Certification Course in Data Science with Machine Learning?

 

The explosion of data in the digital era has revolutionized industries worldwide, making data science and machine learning critical skills for businesses. This certification program offers a structured and practical learning path, covering core concepts and cutting-edge tools to analyze data, build predictive models, and derive actionable insights from complex datasets.
 

 

Program Highlights of Digicrome’s Professional Certification in Data Science with Machine Learning

 

1. Comprehensive Curriculum

Gain an in-depth understanding of essential topics, including:

  • Python Programming for Data Science
  • Exploratory Data Analysis (EDA)
  • Statistical Modeling and Predictive Analytics
  • Machine Learning and AI Fundamentals
  • Big Data Analytics and more!

The curriculum is designed for a smooth progression, gradually introducing advanced concepts to provide a complete understanding of data science and machine learning.

 

Expert Faculty & Mentorship

 

Learn from industry leaders and data science experts who bring real-world insights into the classroom. With access to:

  • Live sessions and hands-on workshops
  • Guidance from top professionals in data science and ML
  • Dedicated program managers to support your learning journey
     

 

3. Hands-On Projects & Real-World Applications

 

The program emphasizes practical knowledge through:

  • Industry-relevant projects and case studies
  • Capstone projects that simulate real-world data science challenges
  • Personalized feedback to ensure skill enhancement

 

4. Networking Opportunities

 

Connect with a global network of professionals, mentors, and industry experts. The program facilitates collaboration and learning through:

  • Virtual meetups
  • Peer-to-peer learning forums
  • Opportunities to work with mentors and data scientists

 

5. Flexible and Personalized Learning Support

 

  • 1:1 Doubt-Clearing Sessions via video calls, emails, or chat
  • Access to a dedicated support team for academic and technical queries
  • Self-paced learning modules to fit your schedule

 

6. Certification from Industry Leaders

 

Earn globally recognized certifications from Digicrome, IBM, and Microsoft, making you stand out in the competitive job market.

Why Enroll in Digicrome’s Professional Certification Course?

  • Gain job-ready skills with practical experience
  • Master data science tools and techniques used by top companies
  • Build your portfolio and gain industry exposure
  • Enjoy lifetime career support with resume-building workshops, mock interviews, and job placement assistance

Embark on Your Data Science Journey

Transform your career with Digicrome’s Professional Certification in Data Science with Machine Learning. Stay ahead in the fast-evolving world of technology and gain a competitive edge in the global job market.

 

📌 Apply Now and take the first step toward becoming a leader in data science and machine learning. Shape your future with confidence!

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Course Includes :

  • Price
    172,500 + GST
  • US Price
    $1999.00
  • Dubai Price
    7352.00AED
  • Certifications
    Yes
  • Language
    English (US)
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Our Course Curriculum

100% Trusted And Golden Opportunities With Key Features That will Help You To Transform Your Career

1 Introduction to Python - print(), input(), Comments, Variables, Built-in Data Types

2 Basics of Python - Strings and its methods, Python Booleans, Operators (Arithmetic, Logical, Comparison, Assignment, Identity, Memebership, Bitwise), Slicing and Indexing

3 Python Data Structures

4 Python Conditional Statements - IF, ELIF, ELSE

5 Loops in Python

6 Python Functions - Creating, Calling, Arguments, Arbitrary Arguments, Keyword Arguments, Arbitrary Keyword Arguments, Positional Arguments, Default Parameters, RETURN, LAMBDA.

7 Python Classes and Objects

8 Miscellaneous - Datetime, RegEx, String Formatting, TRY/EXCEPT

1 NumPy - Numerical Python

2 Data Wrangling using PANDAS

3 Data Visualization Using Matplotlib and Seaborn

4 Web Srcaping using Beautiful Soup

1 Advanced Tutorial on Microsoft Excel

1.1 Introduction to Excel - Formatting, Insertion, Basic Functions (SUM, AVG, etc.)

1.2 Pivot Tables and LOOKUP Functions ( VLOOKUP, HLOOKUP, XLOOKUP, etc.)

1.3 Logical and Statistical Functions

1.4 Chart Data Techniques

1.5 Date/Time, Text, Math Functions

1.6 Advanced Filtering and Sorting

1.7 Summarizing, Importing and Exporting Data from Databases and Web

2.1 Introduction to Databases - (What are Databases), (What is MySQL), (What is RDBMS), (RDBMS v/s NoSQL)

2.2 Data Base Workflows - Understanding Entity Relationship Diagram, Understanding Normalization (1NF, 2NF, 3NF, BCNF)

2.3 Structured Query Language (SQL) - CRUD Operations

2.4 Data Aggregation Functions - (GroupBy), (OrderBy), (HAVING), (COUNT, SUM, MIN, MAX, AVG)

2.5 Joins in SQL - Primary Key and Foreign Key, Constraints, Set Operations, DML - Savepoint, Rollback

3.1 Installation, Setup, Importing CSV and Excel Files, Connecting SQL Databases and Cloud Services

3.2 Data Cleaning and Wrangling - Handling Missing Values, Handling Duplicates, Formatting of Data, Joins in Tableau

3.3 Basic Visualizations - Bar Chart, Line Chart, Pie Chart, Scatter Plot, Geographical Data Visualization on Maps, Dashboards in Tableau

3.4 Advanced Visualizations - Heat Maps, Tree Maps, Boxplots, Histograms, Parameters for interactivity and flexibility, Calculated Fields to create new metrics and dimensions

3.5 Analytics and Statistical Tools - Trend Lines and Forecasting, Clustering Techniques and Distribution Analysis

3.6 Filters, Highlighters, Actions to create interactive dashboards, Dashboard Designs

3.7 Case Study - Real World use case of Tableau for Data Science

4.1 Installation, Setup, Importing Files, Connecting SQL Databases and Cloud Services, Direct Query Methods in Power BI

4.2 Power Query - Data Cleaning and Transformation (Handling Missing Values and Duplicates, Formatting of Data)

4.3 Data Modeling - Calculated Columns, Managing Data Models, Creating Relationship between two tables

4.4 Basic and Advanced Data Analysis Expressions (DAX) Tutorial

4.5 Basic and Advanced Visualizations - (Basic - Bar Charts, Pie Charts, Matrices, Maps, etc.), (Advanced - Custom Visualizations, Slicers, Filters, Waterfall Charts, Funnel Charts, Gauge Charts, etc.)

4.6 Automated Quick Insights and AI Visuals, Dashboard Designs in Power BI

4.7 Case Study - Real World use case of Power BI for Data Science

1 Introduction to Machine Learning

1.1 What is ML, Why ML, Types of ML, (Training, Validation, and Testing Set)

1.2 Train/Test Split, Preprocessing of Data (LabelEncoder, OneHotEncoder), Standardization of Data

1.3 Hyperparameters, Selection and Fine Tuning of Models, (Main Challenges - Overfitting, Underfitting, Poor Quality Data, Irrelavant Features, etc.)

2.1 Descriptive Statistics - Estimates of Location (Mean, Weighted Mean, Trimmed Mean, Median, Weighted Median, Mode, Outliers), Estimates of Variability (Deviations, Variance, Standard Deviation, Mean Absolute Deviation, Median Absolute Deviation, Range, Percentiles, Quantiles, Deciles, Interquartile Range, Degrees of Freedom), Skewness and Kurtosis

2.2 Sampling Techniques - Bias Sample, Population, Random Sampling, Stratified Sampling, Simple Random Sampling, Bootstrap, Resampling

2.3 Inferential Statistics - Confidence Intervals, Normal Distribution (Z-score, QQ-Plot), T-Distrubtion and T-test, Binomial Distribution, Chi-Square Distribution and Chi-Square Test, F-Distribution, F-test, ANOVA Test, Poisson Distribution, Exponential Distribution, Weibull Distribution

2.4 Correlation Coffecient, Coefficient of Determination, Simple Linear Regression in Statistics

3.1 Performance Metrics - Accuracy, Recall, Precision, F1 Score, Confusion Matrix, Classification Report, Precision/Recall Tradeoff, ROC Curve, AOC Curve

3.2 Classification Models - Gradient Descent and Stochastic Gradient Descent, Logistic Regression, K Nearest Neighbors (KNN), Naive Bayes, Support Vector Machines (SVM), Linear Discriminant Analysis (LDA), Decission Trees

3.3 Ensembling Methods - Bagging (Voting Classifer, Cross Validation, etc.), Boosting (XG Boost, Adaboost, etc.), Random Forest Classifer, Stacking

3.4 Advanced Techniques - Hyperparameter Tuning, GridSearchCV, RandomizedSearchCV, Multilabel Classification, L1 and L2 Regularization for overfitting, Handling Class Imabalance

3.5 Classification Project - Real World Use Case

4.1 Introduction - Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, Cost Function and Gradient Descent

4.2 Performance Metrics - Mean Squared Error, Root Mean Squared Error, Mean Absolute Error, etc.

4.3 Challenges - Heteroskedasticity, Non - Normality of Data, Multicollinearity of Data, etc.

4.4 Regression Models - Decision Tree Regressor, Support Vector Machine (SVM), K Nearest Neighbors (KNN)

4.5 Ensemble Models - Cross Validation, Voting Classifier, Random Forest, Bagging and Boosting Methods

4.6 Advanced Techniques - Hyperparameter Tuning, GridSearchCV, RandomizedSearchCV, L1 and L2 Regularization

4.7 Regression Project - Real World Use Case

4.1 Introduction to Unsupervised Learning

4.2 Clustering Methods - KMeans, Hierarchical, Model Based Clustering, DBSCAN Clustering, Anamoly Detection using Gaussian Mixture Models

4.3 Dimensionality Reduction using Principal Component Analysis

4.4 Building and Working of Recommendation Engines
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Internship Program

Identify Your Specialty

Learn Data Tools

Real Data Exposure

Learn to Manage Time

Strengthen Your Resume

Expand Your Network

Build a Strong Portfolio

Get Experts Feedback

Get Internship Certificate

Languages and Tools Covered

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Sample Projects You'll Build

Get hands-on experience with real-world inspired projects. These are some examples of what you'll build during the course.

Trusted by millions of learners around the Globe

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Moments of Honour

In our EdTech journey of more than a decade, we have received numerous awards.
Some of the recent notable awards we have received in analytics are:

  • Successpreneur Award 2023 being the best analytics EdTech business
  • Most Promising Digital Learning Platform 2023 for being one of the most promising digital learning platforms

Our Placed Learners In Different Big Firms

Happy Learners

20,000+

Average Rating

4.8

Average Salary Hike

80%

Average Package

₹ 8 LPA

Our Case Studies

Insights Of All The Learner Recent Learners

Social Media Sentiment Analysis

Analyze social media posts using NLP & set a pipeline for gathering, processing, and categorizing public sentiment as positive, negative, or neutral through custom text analysis.

Create a Predictive Dashboard

Help businesses make informed decisions by creating a predictive dashboard that analyzes past data, forecasts future trends, and enables automatic pattern detection.

Interpret Data with Tableau

Use Tableau to create effective dashboards showing customer behavior, trends, or retail sales, helping any business clearly understand data and make quick, accurate decisions.

Create Multi-Modal AI Assistant

Develop a multi-modal AI assistant that engages through voice/text, identifies faces, and summarizes documents by incorporating natural language processing with computer vision.

iconTESTIMONIALS

What Students Say About
Digicrome Experience

Students love the hands-on learning, expert mentors, and real-world projects that make the Digicrome experience truly exceptional.

Application Process for Digicrome

Our Acknowledged features offerings

1
Career Consultation
Assess eligibility
2
Personalized Guidance
Acceptance letter
3
Easy Registration
Pay booking amount
4
Start Upskilling
Access curriculum
5
Ongoing Support
Mentorship & guidance
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Our Course Comes with Offerings

By Joining Our Program, Underlying Are The Key Featuers You Will Get

Get Lifetime Access to LMS

Get Lifetime Access to LMS

Your growth doesn’t end with the course—and neither does your access. With lifetime entry to our Learning Management System, you can revisit lessons, sharpen your skills, and stay up to date whenever you need. Learn at your pace, on your terms—because real learning is lifelong.

Live Interactive Online Sessions

" Make your weekends count with live sessions guided by experienced industry professionals. These aren’t just classes—they’re your space to ask, discuss, and truly understand. Connect with peers, solve real-world challenges together, and build confidence that lasts beyond the classroom. All scheduled keeping your time and growth in mind.

Live Interactive Online Sessions
Regular Evaluations for better learning

Regular Evaluations for better learning

We don’t just track your progress—we walk with you every step of the way. Through timely check-ins, constructive feedback, and personalised support, we help you understand what’s working and where to improve. It’s not about marks, it’s about momentum—so you keep moving forward with clarity and confidence.
 

Personalized Doubt Sessions

Every learner has unique challenges—and that’s why we offer one-on-one mentor support tailored just for you. From untangling tough topics to guiding your next steps, our mentors are here to listen, support, and keep you moving forward. Because real learning happens when someone’s genuinely there for you.
 

Personalized Doubt Sessions
Hands-On Projects & Case Studies

Hands-On Projects & Case Studies

Whichever path you choose—be it Data Science, AI, or Analytics—you won’t just study concepts, you’ll apply them. Through practical projects inspired by real industry scenarios, you’ll build the skills and confidence to solve challenges that companies face every day. It’s not just learning—it’s preparing for what comes next.
 

Focused Learning Tracks

Your career journey is unique—and your learning should reflect that. Choose a course that matches your goals, and dive deep into the skills that matter most in your domain. Whether you're drawn to tech, business, or the creative world, you'll gain focused expertise that sets you up for success, your way
 

Focused Learning Tracks
Interview Preparation

Interview Preparation

We don’t just help you learn—we help you land the job. With personalised career guidance and realistic mock interviews, you’ll get the support you need to present your strengths, handle tough questions, and walk into every interview prepared and self-assured. Because your success is our goal, right from day one.

Our FAQs

Imperative FAQs About Us!

Become a part of this professional certification course in Data Science with Machine Learning. And within six months, you will be skilled at advanced level, starting from the basics in tools and techniques needed in this field, like Python and Big Data, along with certifications from Digichrome, IBM, and Microsoft.

This course can be taken up by anyone who is interested in data science. You can be an early career professional, a recent graduate, an analyst, or someone looking to switch careers. The flexible structure allows both beginners and experienced learners to grasp and begin their careers in this field.

The course is diversified. It ensures you learn not just theory but practically, using live sessions, hands-on projects, expert-led training, and career assistance. The structure is divided into modules covering Python, SQL, etc. It takes you from the basics to real-world understanding.

Within the six-month time frame, you will be skilled enough to help companies make business decisions with your data insights. You will be skilled at data visualization, wrangling, model building, machine learning, etc. You will be a professional data analyzer with predictive model understanding.

No previous background in data science is needed. The requirement is to be curious enough in data and have a bachelor's degree from any accredited institution. The course starts from fundamentals, so it's free to be taken by a complete beginner. Moreover, it can be taken up by any intermediate learner as well who is looking for better career opportunities and growth.

No previous background in data science is needed. The requirement is to be curious enough in data and have a bachelor's degree from any accredited institution. The course starts from fundamentals, so it can be taken by a complete beginner or any professional as well looking for better career opportunities and growth.

We help you through career assistance, including resume preparation, mock interviews, and one-on-one guidance. With placement support and partnerships with 500+ companies, you get hired in roles matching your interests. We ensure a smooth transition into data science roles.